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1,719
|
hockey
|
bird:train.json:7786
|
In the year 1958, what is the total number of players that became hall of famers?
|
SELECT COUNT(hofID) FROM HOF WHERE category = 'Player' AND year = 1958
|
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"O",
"O",
"O",
"O",
"O",
"O"
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1,720
|
assets_maintenance
|
spider:train_spider.json:3156
|
Which assets did not incur any fault log? List the asset model.
|
SELECT asset_model FROM Assets WHERE asset_id NOT IN (SELECT asset_id FROM Fault_Log)
|
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"type": "column",
"value": "asset_id"
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"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
1,721
|
donor
|
bird:train.json:3221
|
How to pay the donation of the project that teacher "822b7b8768c17456fdce78b65abcc18e" created?
|
SELECT T2.payment_method FROM projects AS T1 INNER JOIN donations AS T2 ON T1.projectid = T2.projectid WHERE T1.teacher_acctid = '822b7b8768c17456fdce78b65abcc18e'
|
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{
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"type": "column",
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{
"id": 1,
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"value": "projects"
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"B-TABLE",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O"
] |
1,722
|
local_govt_in_alabama
|
spider:train_spider.json:2141
|
What are all the the participant ids, type code and details?
|
SELECT Participant_ID , Participant_Type_Code , Participant_Details FROM Participants
|
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"id": 2,
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{
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"value": "participant_details"
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{
"id": 1,
"type": "column",
"value": "participant_id"
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{
"id": 0,
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"value": "participants"
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[
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"B-COLUMN",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O"
] |
1,723
|
bike_share_1
|
bird:train.json:9022
|
Write down the times when there is no available bike to borrow in a station. List down the stations name and location coordinate.
|
SELECT T2.time, T1.name, T1.lat, T1.long FROM station AS T1 INNER JOIN status AS T2 ON T2.station_id = T1.id WHERE T2.bikes_available = 0
|
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{
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{
"id": 8,
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"value": "station_id"
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{
"id": 4,
"type": "table",
"value": "station"
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{
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"value": "status"
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{
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{
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"value": "name"
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{
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"type": "column",
"value": "long"
},
{
"id": 2,
"type": "column",
"value": "lat"
},
{
"id": 9,
"type": "column",
"value": "id"
},
{
"id": 7,
"type": "value",
"value": "0"
}
] |
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[
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"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
1,724
|
shipping
|
bird:train.json:5625
|
Name the customer who sent the shipment to Oak Park.
|
SELECT T2.cust_name FROM shipment AS T1 INNER JOIN customer AS T2 ON T1.cust_id = T2.cust_id INNER JOIN city AS T3 ON T3.city_id = T1.city_id WHERE T3.city_name = 'Oak Park'
|
[
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"Park",
"."
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[
{
"id": 0,
"type": "column",
"value": "cust_name"
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{
"id": 2,
"type": "column",
"value": "city_name"
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{
"id": 3,
"type": "value",
"value": "Oak Park"
},
{
"id": 4,
"type": "table",
"value": "shipment"
},
{
"id": 5,
"type": "table",
"value": "customer"
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{
"id": 6,
"type": "column",
"value": "city_id"
},
{
"id": 7,
"type": "column",
"value": "cust_id"
},
{
"id": 1,
"type": "table",
"value": "city"
}
] |
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"O",
"O",
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"O",
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"I-VALUE",
"O"
] |
1,725
|
authors
|
bird:train.json:3546
|
Find the paper ID, title, published year and journal's full name of the paper which included the most number in author.
|
SELECT T1.Id, T1.Title, T1.Year, T3.FullName FROM Paper AS T1 INNER JOIN PaperAuthor AS T2 ON T1.Id = T2.PaperId INNER JOIN Journal AS T3 ON T1.JournalId = T3.Id GROUP BY T2.AuthorId ORDER BY COUNT(T2.AuthorId) DESC LIMIT 1
|
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{
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{
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{
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"type": "column",
"value": "year"
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{
"id": 1,
"type": "column",
"value": "id"
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"O",
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"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
1,726
|
real_estate_rentals
|
bird:test.json:1440
|
When did the user with login name ratione register?
|
SELECT date_registered FROM Users WHERE login_name = 'ratione';
|
[
"When",
"did",
"the",
"user",
"with",
"login",
"name",
"ratione",
"register",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "date_registered"
},
{
"id": 2,
"type": "column",
"value": "login_name"
},
{
"id": 3,
"type": "value",
"value": "ratione"
},
{
"id": 0,
"type": "table",
"value": "users"
}
] |
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{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"B-COLUMN",
"O"
] |
1,727
|
superstore
|
bird:train.json:2404
|
How many office supply orders were made by Cindy Stewart in the south superstore?
|
SELECT COUNT(*) FROM south_superstore AS T1 INNER JOIN people AS T2 ON T1.`Customer ID` = T2.`Customer ID` INNER JOIN product AS T3 ON T3.`Product ID` = T1.`Product ID` WHERE T3.Category = 'Office Supplies' AND T2.`Customer Name` = 'Cindy Stewart'
|
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"?"
] |
[
{
"id": 1,
"type": "table",
"value": "south_superstore"
},
{
"id": 5,
"type": "value",
"value": "Office Supplies"
},
{
"id": 6,
"type": "column",
"value": "Customer Name"
},
{
"id": 7,
"type": "value",
"value": "Cindy Stewart"
},
{
"id": 8,
"type": "column",
"value": "Customer ID"
},
{
"id": 3,
"type": "column",
"value": "Product ID"
},
{
"id": 4,
"type": "column",
"value": "category"
},
{
"id": 0,
"type": "table",
"value": "product"
},
{
"id": 2,
"type": "table",
"value": "people"
}
] |
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13
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{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
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] |
[
"O",
"O",
"B-VALUE",
"I-VALUE",
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"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O"
] |
1,728
|
assets_maintenance
|
spider:train_spider.json:3145
|
Among those engineers who have visited, which engineer makes the least number of visits? List the engineer id, first name and last name.
|
SELECT T1.engineer_id , T1.first_name , T1.last_name FROM Maintenance_Engineers AS T1 JOIN Engineer_Visits AS T2 ON T1.engineer_id = T2.engineer_id GROUP BY T1.engineer_id ORDER BY count(*) ASC LIMIT 1
|
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"d",
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"name",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "maintenance_engineers"
},
{
"id": 4,
"type": "table",
"value": "engineer_visits"
},
{
"id": 0,
"type": "column",
"value": "engineer_id"
},
{
"id": 1,
"type": "column",
"value": "first_name"
},
{
"id": 2,
"type": "column",
"value": "last_name"
}
] |
[
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18,
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20
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{
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22,
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26
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{
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},
{
"entity_id": 18,
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},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"B-TABLE",
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"B-TABLE",
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"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
1,729
|
airline
|
bird:train.json:5848
|
For the flight from ATL to PHL on 2018/8/1 that scheduled local departure time as "2040", which air carrier does this flight belong to?
|
SELECT T2.Description FROM Airlines AS T1 INNER JOIN `Air Carriers` AS T2 ON T1.OP_CARRIER_AIRLINE_ID = T2.Code WHERE T1.FL_DATE = '2018/8/1' AND T1.ORIGIN = 'ATL' AND T1.DEST = 'PHL' AND T1.CRS_DEP_TIME = '2040' GROUP BY T2.Description
|
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",",
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"?"
] |
[
{
"id": 3,
"type": "column",
"value": "op_carrier_airline_id"
},
{
"id": 2,
"type": "table",
"value": "Air Carriers"
},
{
"id": 11,
"type": "column",
"value": "crs_dep_time"
},
{
"id": 0,
"type": "column",
"value": "description"
},
{
"id": 1,
"type": "table",
"value": "airlines"
},
{
"id": 6,
"type": "value",
"value": "2018/8/1"
},
{
"id": 5,
"type": "column",
"value": "fl_date"
},
{
"id": 7,
"type": "column",
"value": "origin"
},
{
"id": 4,
"type": "column",
"value": "code"
},
{
"id": 9,
"type": "column",
"value": "dest"
},
{
"id": 12,
"type": "value",
"value": "2040"
},
{
"id": 8,
"type": "value",
"value": "ATL"
},
{
"id": 10,
"type": "value",
"value": "PHL"
}
] |
[
{
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"token_idxs": []
},
{
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},
{
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},
{
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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-VALUE",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
1,730
|
video_games
|
bird:train.json:3369
|
What is the release year of the game that gained 350000 sales in North America?
|
SELECT T3.release_year FROM region AS T1 INNER JOIN region_sales AS T2 ON T1.id = T2.region_id INNER JOIN game_platform AS T3 ON T2.game_platform_id = T3.id WHERE T2.num_sales * 100000 = 350000 AND T1.region_name = 'North America'
|
[
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"350000",
"sales",
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"North",
"America",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "game_platform_id"
},
{
"id": 1,
"type": "table",
"value": "game_platform"
},
{
"id": 8,
"type": "value",
"value": "North America"
},
{
"id": 0,
"type": "column",
"value": "release_year"
},
{
"id": 3,
"type": "table",
"value": "region_sales"
},
{
"id": 7,
"type": "column",
"value": "region_name"
},
{
"id": 9,
"type": "column",
"value": "region_id"
},
{
"id": 10,
"type": "column",
"value": "num_sales"
},
{
"id": 2,
"type": "table",
"value": "region"
},
{
"id": 6,
"type": "value",
"value": "350000"
},
{
"id": 11,
"type": "value",
"value": "100000"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
[
{
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3,
4
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},
{
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{
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{
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{
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{
"entity_id": 15,
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},
{
"entity_id": 16,
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{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
1,731
|
department_management
|
spider:train_spider.json:12
|
What are the distinct ages of the heads who are acting?
|
SELECT DISTINCT T1.age FROM management AS T2 JOIN head AS T1 ON T1.head_id = T2.head_id WHERE T2.temporary_acting = 'Yes'
|
[
"What",
"are",
"the",
"distinct",
"ages",
"of",
"the",
"heads",
"who",
"are",
"acting",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "temporary_acting"
},
{
"id": 1,
"type": "table",
"value": "management"
},
{
"id": 5,
"type": "column",
"value": "head_id"
},
{
"id": 2,
"type": "table",
"value": "head"
},
{
"id": 0,
"type": "column",
"value": "age"
},
{
"id": 4,
"type": "value",
"value": "Yes"
}
] |
[
{
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"token_idxs": [
4
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},
{
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},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
9,
10
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},
{
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},
{
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{
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},
{
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{
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{
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{
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},
{
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"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
1,732
|
retails
|
bird:train.json:6723
|
Identify the names of the top 3 customers with the highest number of orders of all time and calculate for the average total price per order of each customers.
|
SELECT T.c_name, T.res FROM ( SELECT T2.c_name, SUM(T1.o_totalprice) / COUNT(T1.o_orderkey) AS res , COUNT(T1.o_orderkey) AS num FROM orders AS T1 INNER JOIN customer AS T2 ON T1.o_custkey = T2.c_custkey GROUP BY T1.o_custkey ) AS T ORDER BY T.num DESC LIMIT 3
|
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"the",
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"total",
"price",
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"."
] |
[
{
"id": 8,
"type": "column",
"value": "o_totalprice"
},
{
"id": 6,
"type": "column",
"value": "o_orderkey"
},
{
"id": 3,
"type": "column",
"value": "o_custkey"
},
{
"id": 7,
"type": "column",
"value": "c_custkey"
},
{
"id": 5,
"type": "table",
"value": "customer"
},
{
"id": 0,
"type": "column",
"value": "c_name"
},
{
"id": 4,
"type": "table",
"value": "orders"
},
{
"id": 1,
"type": "column",
"value": "res"
},
{
"id": 2,
"type": "column",
"value": "num"
}
] |
[
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{
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},
{
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},
{
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{
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{
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{
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"token_idxs": []
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{
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
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"O",
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"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
1,733
|
mondial_geo
|
bird:train.json:8416
|
Which river with its mouth in the Donau River and a length greater than 500 km is located in Slovenia?
|
SELECT T2.River FROM country AS T1 INNER JOIN geo_river AS T2 ON T1.Code = T2.Country WHERE T1.Name = 'Slovenia' AND T2.River IN ( SELECT NAME FROM river WHERE Length > 500 AND River = 'Donau' )
|
[
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"and",
"a",
"length",
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"500",
"km",
"is",
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"in",
"Slovenia",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "geo_river"
},
{
"id": 6,
"type": "value",
"value": "Slovenia"
},
{
"id": 1,
"type": "table",
"value": "country"
},
{
"id": 4,
"type": "column",
"value": "country"
},
{
"id": 8,
"type": "column",
"value": "length"
},
{
"id": 0,
"type": "column",
"value": "river"
},
{
"id": 7,
"type": "table",
"value": "river"
},
{
"id": 10,
"type": "value",
"value": "Donau"
},
{
"id": 3,
"type": "column",
"value": "code"
},
{
"id": 5,
"type": "column",
"value": "name"
},
{
"id": 9,
"type": "value",
"value": "500"
}
] |
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{
"entity_id": 10,
"token_idxs": [
7
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 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",
"B-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
1,734
|
warehouse_1
|
bird:test.json:1696
|
What is the content with the greatest value across all boxes?
|
SELECT CONTENTS FROM boxes ORDER BY value DESC LIMIT 1
|
[
"What",
"is",
"the",
"content",
"with",
"the",
"greatest",
"value",
"across",
"all",
"boxes",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "contents"
},
{
"id": 0,
"type": "table",
"value": "boxes"
},
{
"id": 2,
"type": "column",
"value": "value"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
1,735
|
activity_1
|
spider:train_spider.json:6745
|
Which rank has the smallest number of faculty members?
|
SELECT rank FROM Faculty GROUP BY rank ORDER BY count(*) ASC LIMIT 1
|
[
"Which",
"rank",
"has",
"the",
"smallest",
"number",
"of",
"faculty",
"members",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "faculty"
},
{
"id": 1,
"type": "column",
"value": "rank"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"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",
"O",
"B-TABLE",
"O",
"O"
] |
1,736
|
image_and_language
|
bird:train.json:7516
|
What is the prediction relationship class id of the tallest image?
|
SELECT T1.PRED_CLASS_ID FROM IMG_REL AS T1 INNER JOIN IMG_OBJ AS T2 ON T1.IMG_ID = T2.IMG_ID ORDER BY T2.H DESC LIMIT 1
|
[
"What",
"is",
"the",
"prediction",
"relationship",
"class",
"i",
"d",
"of",
"the",
"tallest",
"image",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "pred_class_id"
},
{
"id": 1,
"type": "table",
"value": "img_rel"
},
{
"id": 2,
"type": "table",
"value": "img_obj"
},
{
"id": 4,
"type": "column",
"value": "img_id"
},
{
"id": 3,
"type": "column",
"value": "h"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5,
6,
7
]
},
{
"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",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
1,737
|
cookbook
|
bird:train.json:8929
|
Calculate the percentage of recipes with no cholesterol included and have a cooking time less than 20 minutes among all recipes.
|
SELECT CAST(SUM(CASE WHEN T1.cook_min < 20 AND T2.cholestrl = 0 THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(*) FROM Recipe AS T1 INNER JOIN Nutrition AS T2 ON T1.recipe_id = T2.recipe_id
|
[
"Calculate",
"the",
"percentage",
"of",
"recipes",
"with",
"no",
"cholesterol",
"included",
"and",
"have",
"a",
"cooking",
"time",
"less",
"than",
"20",
"minutes",
"among",
"all",
"recipes",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "nutrition"
},
{
"id": 2,
"type": "column",
"value": "recipe_id"
},
{
"id": 8,
"type": "column",
"value": "cholestrl"
},
{
"id": 6,
"type": "column",
"value": "cook_min"
},
{
"id": 0,
"type": "table",
"value": "recipe"
},
{
"id": 3,
"type": "value",
"value": "100"
},
{
"id": 7,
"type": "value",
"value": "20"
},
{
"id": 4,
"type": "value",
"value": "0"
},
{
"id": 5,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
20
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
16
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
12
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
7
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
1,738
|
chicago_crime
|
bird:train.json:8710
|
What are the full names of the top 5 most crowded ward aldermen?
|
SELECT alderman_first_name, alderman_last_name FROM Ward ORDER BY Population DESC LIMIT 5
|
[
"What",
"are",
"the",
"full",
"names",
"of",
"the",
"top",
"5",
"most",
"crowded",
"ward",
"aldermen",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "alderman_first_name"
},
{
"id": 2,
"type": "column",
"value": "alderman_last_name"
},
{
"id": 3,
"type": "column",
"value": "population"
},
{
"id": 0,
"type": "table",
"value": "ward"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
11
]
},
{
"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",
"O",
"O"
] |
1,739
|
sakila_1
|
spider:train_spider.json:2926
|
What is the most popular first name of the actors?
|
SELECT first_name FROM actor GROUP BY first_name ORDER BY count(*) DESC LIMIT 1
|
[
"What",
"is",
"the",
"most",
"popular",
"first",
"name",
"of",
"the",
"actors",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "first_name"
},
{
"id": 0,
"type": "table",
"value": "actor"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
"token_idxs": [
5,
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
1,740
|
hr_1
|
spider:train_spider.json:3456
|
Give the country id and corresponding count of cities in each country.
|
SELECT country_id , COUNT(*) FROM locations GROUP BY country_id
|
[
"Give",
"the",
"country",
"i",
"d",
"and",
"corresponding",
"count",
"of",
"cities",
"in",
"each",
"country",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "country_id"
},
{
"id": 0,
"type": "table",
"value": "locations"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2,
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",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
1,741
|
shipping
|
bird:train.json:5638
|
Give the full name of driver who transported the items on 3/2/2016.
|
SELECT T2.first_name, T2.last_name FROM shipment AS T1 INNER JOIN driver AS T2 ON T1.driver_id = T2.driver_id WHERE T1.ship_date = '2016-03-02'
|
[
"Give",
"the",
"full",
"name",
"of",
"driver",
"who",
"transported",
"the",
"items",
"on",
"3/2/2016",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "first_name"
},
{
"id": 5,
"type": "value",
"value": "2016-03-02"
},
{
"id": 1,
"type": "column",
"value": "last_name"
},
{
"id": 4,
"type": "column",
"value": "ship_date"
},
{
"id": 6,
"type": "column",
"value": "driver_id"
},
{
"id": 2,
"type": "table",
"value": "shipment"
},
{
"id": 3,
"type": "table",
"value": "driver"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
1,742
|
movies_4
|
bird:train.json:434
|
For the movie "Reign of Fire", which department was Marcia Ross in?
|
SELECT T4.department_name FROM movie AS T1 INNER JOIN movie_crew AS T2 ON T1.movie_id = T2.movie_id INNER JOIN person AS T3 ON T2.person_id = T3.person_id INNER JOIN department AS T4 ON T2.department_id = T4.department_id WHERE T3.person_name = 'Marcia Ross' AND T1.title = 'Reign of Fire'
|
[
"For",
"the",
"movie",
"\"",
"Reign",
"of",
"Fire",
"\"",
",",
"which",
"department",
"was",
"Marcia",
"Ross",
"in",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "department_name"
},
{
"id": 3,
"type": "column",
"value": "department_id"
},
{
"id": 7,
"type": "value",
"value": "Reign of Fire"
},
{
"id": 4,
"type": "column",
"value": "person_name"
},
{
"id": 5,
"type": "value",
"value": "Marcia Ross"
},
{
"id": 1,
"type": "table",
"value": "department"
},
{
"id": 9,
"type": "table",
"value": "movie_crew"
},
{
"id": 10,
"type": "column",
"value": "person_id"
},
{
"id": 11,
"type": "column",
"value": "movie_id"
},
{
"id": 2,
"type": "table",
"value": "person"
},
{
"id": 6,
"type": "column",
"value": "title"
},
{
"id": 8,
"type": "table",
"value": "movie"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
10
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
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{
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},
{
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12,
13
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},
{
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},
{
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4,
5,
6
]
},
{
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2
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},
{
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{
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{
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{
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},
{
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},
{
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"token_idxs": []
},
{
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},
{
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},
{
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O"
] |
1,744
|
retail_world
|
bird:train.json:6373
|
What is the title of the employee with the highest number of territories in charge?
|
SELECT T1.Title FROM Employees AS T1 INNER JOIN EmployeeTerritories AS T2 ON T1.EmployeeID = T2.EmployeeID GROUP BY T1.Title ORDER BY COUNT(T2.TerritoryID) DESC LIMIT 1
|
[
"What",
"is",
"the",
"title",
"of",
"the",
"employee",
"with",
"the",
"highest",
"number",
"of",
"territories",
"in",
"charge",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "employeeterritories"
},
{
"id": 4,
"type": "column",
"value": "territoryid"
},
{
"id": 3,
"type": "column",
"value": "employeeid"
},
{
"id": 1,
"type": "table",
"value": "employees"
},
{
"id": 0,
"type": "column",
"value": "title"
}
] |
[
{
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3
]
},
{
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6
]
},
{
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},
{
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},
{
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12
]
},
{
"entity_id": 5,
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},
{
"entity_id": 6,
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},
{
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{
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},
{
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},
{
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},
{
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},
{
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},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
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},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O"
] |
1,745
|
legislator
|
bird:train.json:4856
|
State the address of Amy Klobuchar at the term of 4th of January 2001.
|
SELECT T2.address FROM current AS T1 INNER JOIN `current-terms` AS T2 ON T1.bioguide_id = T2.bioguide WHERE T1.first_name = 'Amy' AND T1.last_name = 'Klobuchar' AND T2.start = '2001-04-01'
|
[
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"of",
"Amy",
"Klobuchar",
"at",
"the",
"term",
"of",
"4th",
"of",
"January",
"2001",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "current-terms"
},
{
"id": 3,
"type": "column",
"value": "bioguide_id"
},
{
"id": 5,
"type": "column",
"value": "first_name"
},
{
"id": 10,
"type": "value",
"value": "2001-04-01"
},
{
"id": 7,
"type": "column",
"value": "last_name"
},
{
"id": 8,
"type": "value",
"value": "Klobuchar"
},
{
"id": 4,
"type": "column",
"value": "bioguide"
},
{
"id": 0,
"type": "column",
"value": "address"
},
{
"id": 1,
"type": "table",
"value": "current"
},
{
"id": 9,
"type": "column",
"value": "start"
},
{
"id": 6,
"type": "value",
"value": "Amy"
}
] |
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},
{
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{
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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": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
1,747
|
warehouse_1
|
bird:test.json:1738
|
For each location, what are the total, average, and maximum capacities of warehouses?
|
SELECT sum(capacity) , avg(capacity) , max(capacity) , LOCATION FROM warehouses GROUP BY LOCATION
|
[
"For",
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"location",
",",
"what",
"are",
"the",
"total",
",",
"average",
",",
"and",
"maximum",
"capacities",
"of",
"warehouses",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "warehouses"
},
{
"id": 1,
"type": "column",
"value": "location"
},
{
"id": 2,
"type": "column",
"value": "capacity"
}
] |
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15
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2
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13
]
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{
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{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
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"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",
"B-COLUMN",
"O",
"B-TABLE",
"O"
] |
1,748
|
sakila_1
|
spider:train_spider.json:2958
|
What is the total amount of all payments?
|
SELECT sum(amount) FROM payment
|
[
"What",
"is",
"the",
"total",
"amount",
"of",
"all",
"payments",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "payment"
},
{
"id": 1,
"type": "column",
"value": "amount"
}
] |
[
{
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},
{
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4
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{
"entity_id": 3,
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},
{
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},
{
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},
{
"entity_id": 6,
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{
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},
{
"entity_id": 8,
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},
{
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},
{
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},
{
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},
{
"entity_id": 12,
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},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
1,749
|
professional_basketball
|
bird:train.json:2834
|
Please list the top ten teams with the highest scores in 2000.
|
SELECT tmID FROM players_teams WHERE year = 2000 GROUP BY tmID ORDER BY SUM(PostPoints) DESC LIMIT 10
|
[
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"list",
"the",
"top",
"ten",
"teams",
"with",
"the",
"highest",
"scores",
"in",
"2000",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "players_teams"
},
{
"id": 4,
"type": "column",
"value": "postpoints"
},
{
"id": 1,
"type": "column",
"value": "tmid"
},
{
"id": 2,
"type": "column",
"value": "year"
},
{
"id": 3,
"type": "value",
"value": "2000"
}
] |
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{
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{
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11
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{
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},
{
"entity_id": 14,
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},
{
"entity_id": 15,
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},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
1,750
|
world_development_indicators
|
bird:train.json:2203
|
What is the percentage of countries in the Middle East and North Africa that have finished reporting on their real external debt?
|
SELECT CAST(SUM(CASE WHEN ExternalDebtReportingStatus = 'Actual' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(CountryCode) FROM Country WHERE region = 'Middle East & North Africa'
|
[
"What",
"is",
"the",
"percentage",
"of",
"countries",
"in",
"the",
"Middle",
"East",
"and",
"North",
"Africa",
"that",
"have",
"finished",
"reporting",
"on",
"their",
"real",
"external",
"debt",
"?"
] |
[
{
"id": 7,
"type": "column",
"value": "externaldebtreportingstatus"
},
{
"id": 2,
"type": "value",
"value": "Middle East & North Africa"
},
{
"id": 4,
"type": "column",
"value": "countrycode"
},
{
"id": 0,
"type": "table",
"value": "country"
},
{
"id": 1,
"type": "column",
"value": "region"
},
{
"id": 8,
"type": "value",
"value": "Actual"
},
{
"id": 3,
"type": "value",
"value": "100"
},
{
"id": 5,
"type": "value",
"value": "0"
},
{
"id": 6,
"type": "value",
"value": "1"
}
] |
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"token_idxs": [
5
]
},
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{
"entity_id": 2,
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9,
10,
11,
12
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"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",
"B-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
1,751
|
video_games
|
bird:train.json:3445
|
Calculate the average game sales for the PS2 platform.
|
SELECT SUM(T3.num_sales * 100000) / COUNT(T1.id) FROM platform AS T1 INNER JOIN game_platform AS T2 ON T1.id = T2.platform_id INNER JOIN region_sales AS T3 ON T2.id = T3.game_platform_id WHERE T1.platform_name = 'PS2'
|
[
"Calculate",
"the",
"average",
"game",
"sales",
"for",
"the",
"PS2",
"platform",
"."
] |
[
{
"id": 6,
"type": "column",
"value": "game_platform_id"
},
{
"id": 1,
"type": "column",
"value": "platform_name"
},
{
"id": 4,
"type": "table",
"value": "game_platform"
},
{
"id": 0,
"type": "table",
"value": "region_sales"
},
{
"id": 7,
"type": "column",
"value": "platform_id"
},
{
"id": 8,
"type": "column",
"value": "num_sales"
},
{
"id": 3,
"type": "table",
"value": "platform"
},
{
"id": 9,
"type": "value",
"value": "100000"
},
{
"id": 2,
"type": "value",
"value": "PS2"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
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},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
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{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
1,752
|
books
|
bird:train.json:5963
|
What is the title of the most expensive book?
|
SELECT T1.title FROM book AS T1 INNER JOIN order_line AS T2 ON T1.book_id = T2.book_id ORDER BY T2.price DESC LIMIT 1
|
[
"What",
"is",
"the",
"title",
"of",
"the",
"most",
"expensive",
"book",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "order_line"
},
{
"id": 4,
"type": "column",
"value": "book_id"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 3,
"type": "column",
"value": "price"
},
{
"id": 1,
"type": "table",
"value": "book"
}
] |
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"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
1,754
|
movies_4
|
bird:train.json:509
|
Find out the language ID of the movie with the highest popularity.
|
SELECT T2.language_id FROM movie AS T1 INNER JOIN movie_languages AS T2 ON T1.movie_id = T2.movie_id ORDER BY T1.popularity DESC LIMIT 1
|
[
"Find",
"out",
"the",
"language",
"ID",
"of",
"the",
"movie",
"with",
"the",
"highest",
"popularity",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "movie_languages"
},
{
"id": 0,
"type": "column",
"value": "language_id"
},
{
"id": 3,
"type": "column",
"value": "popularity"
},
{
"id": 4,
"type": "column",
"value": "movie_id"
},
{
"id": 1,
"type": "table",
"value": "movie"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"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-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
1,755
|
simpson_episodes
|
bird:train.json:4280
|
How many votes of 5-star did the episode "Lisa the Drama Queen" receive?
|
SELECT SUM(T2.votes) FROM Episode AS T1 INNER JOIN Vote AS T2 ON T2.episode_id = T1.episode_id WHERE T1.title = 'Lisa the Drama Queen' AND T2.stars = 5;
|
[
"How",
"many",
"votes",
"of",
"5",
"-",
"star",
"did",
"the",
"episode",
"\"",
"Lisa",
"the",
"Drama",
"Queen",
"\"",
"receive",
"?"
] |
[
{
"id": 5,
"type": "value",
"value": "Lisa the Drama Queen"
},
{
"id": 3,
"type": "column",
"value": "episode_id"
},
{
"id": 0,
"type": "table",
"value": "episode"
},
{
"id": 2,
"type": "column",
"value": "votes"
},
{
"id": 4,
"type": "column",
"value": "title"
},
{
"id": 6,
"type": "column",
"value": "stars"
},
{
"id": 1,
"type": "table",
"value": "vote"
},
{
"id": 7,
"type": "value",
"value": "5"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"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": [
11,
12,
13,
14
]
},
{
"entity_id": 6,
"token_idxs": [
6
]
},
{
"entity_id": 7,
"token_idxs": [
4
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O"
] |
1,756
|
products_gen_characteristics
|
spider:train_spider.json:5598
|
What are characteristic names used at least twice across all products?
|
SELECT t3.characteristic_name FROM products AS t1 JOIN product_characteristics AS t2 ON t1.product_id = t2.product_id JOIN CHARACTERISTICS AS t3 ON t2.characteristic_id = t3.characteristic_id GROUP BY t3.characteristic_name HAVING count(*) >= 2
|
[
"What",
"are",
"characteristic",
"names",
"used",
"at",
"least",
"twice",
"across",
"all",
"products",
"?"
] |
[
{
"id": 4,
"type": "table",
"value": "product_characteristics"
},
{
"id": 0,
"type": "column",
"value": "characteristic_name"
},
{
"id": 5,
"type": "column",
"value": "characteristic_id"
},
{
"id": 1,
"type": "table",
"value": "characteristics"
},
{
"id": 6,
"type": "column",
"value": "product_id"
},
{
"id": 3,
"type": "table",
"value": "products"
},
{
"id": 2,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
1,757
|
art_1
|
bird:test.json:1290
|
What are the average height and width of paintings grouped by painters and ordered by name?
|
SELECT avg(height_mm) , avg(width_mm) , painterID FROM paintings GROUP BY painterID ORDER BY title
|
[
"What",
"are",
"the",
"average",
"height",
"and",
"width",
"of",
"paintings",
"grouped",
"by",
"painters",
"and",
"ordered",
"by",
"name",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "paintings"
},
{
"id": 1,
"type": "column",
"value": "painterid"
},
{
"id": 3,
"type": "column",
"value": "height_mm"
},
{
"id": 4,
"type": "column",
"value": "width_mm"
},
{
"id": 2,
"type": "column",
"value": "title"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
11
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
1,758
|
company_1
|
spider:train_spider.json:2132
|
find all dependent names who have a spouse relation with some employee.
|
SELECT Dependent_name FROM dependent WHERE relationship = 'Spouse'
|
[
"find",
"all",
"dependent",
"names",
"who",
"have",
"a",
"spouse",
"relation",
"with",
"some",
"employee",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "dependent_name"
},
{
"id": 2,
"type": "column",
"value": "relationship"
},
{
"id": 0,
"type": "table",
"value": "dependent"
},
{
"id": 3,
"type": "value",
"value": "Spouse"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
1,759
|
club_1
|
spider:train_spider.json:4295
|
Who is the president of the club "Bootup Baltimore"? Give me the first and last name.
|
SELECT t3.fname , t3.lname FROM club AS t1 JOIN member_of_club AS t2 ON t1.clubid = t2.clubid JOIN student AS t3 ON t2.stuid = t3.stuid WHERE t1.clubname = "Bootup Baltimore" AND t2.position = "President"
|
[
"Who",
"is",
"the",
"president",
"of",
"the",
"club",
"\"",
"Bootup",
"Baltimore",
"\"",
"?",
"Give",
"me",
"the",
"first",
"and",
"last",
"name",
"."
] |
[
{
"id": 7,
"type": "column",
"value": "Bootup Baltimore"
},
{
"id": 4,
"type": "table",
"value": "member_of_club"
},
{
"id": 9,
"type": "column",
"value": "President"
},
{
"id": 6,
"type": "column",
"value": "clubname"
},
{
"id": 8,
"type": "column",
"value": "position"
},
{
"id": 2,
"type": "table",
"value": "student"
},
{
"id": 10,
"type": "column",
"value": "clubid"
},
{
"id": 0,
"type": "column",
"value": "fname"
},
{
"id": 1,
"type": "column",
"value": "lname"
},
{
"id": 5,
"type": "column",
"value": "stuid"
},
{
"id": 3,
"type": "table",
"value": "club"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
18
]
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"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": [
8,
9
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
1,760
|
architecture
|
spider:train_spider.json:6959
|
What is the most common mill type, and how many are there?
|
SELECT TYPE , count(*) FROM mill GROUP BY TYPE ORDER BY count(*) DESC LIMIT 1
|
[
"What",
"is",
"the",
"most",
"common",
"mill",
"type",
",",
"and",
"how",
"many",
"are",
"there",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "mill"
},
{
"id": 1,
"type": "column",
"value": "type"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"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",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
1,761
|
chicago_crime
|
bird:train.json:8735
|
How many neighborhoods can be found in the Forest Glen community area?
|
SELECT SUM(CASE WHEN T2.community_area_name = 'Forest Glen' THEN 1 ELSE 0 END) FROM Neighborhood AS T1 INNER JOIN Community_Area AS T2 ON T1.community_area_no = T2.community_area_no
|
[
"How",
"many",
"neighborhoods",
"can",
"be",
"found",
"in",
"the",
"Forest",
"Glen",
"community",
"area",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "community_area_name"
},
{
"id": 2,
"type": "column",
"value": "community_area_no"
},
{
"id": 1,
"type": "table",
"value": "community_area"
},
{
"id": 0,
"type": "table",
"value": "neighborhood"
},
{
"id": 6,
"type": "value",
"value": "Forest Glen"
},
{
"id": 3,
"type": "value",
"value": "0"
},
{
"id": 4,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
10,
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": [
8,
9
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"B-TABLE",
"I-TABLE",
"O"
] |
1,762
|
movie_3
|
bird:train.json:9250
|
Give the full name of the actor who acted in the most number of movies?
|
SELECT T.first_name, T.last_name FROM ( SELECT T2.first_name, T2.last_name, COUNT(T1.film_id) AS num FROM film_actor AS T1 INNER JOIN actor AS T2 ON T1.actor_id = T2.actor_id GROUP BY T2.first_name, T2.last_name ) AS T ORDER BY T.num DESC LIMIT 1
|
[
"Give",
"the",
"full",
"name",
"of",
"the",
"actor",
"who",
"acted",
"in",
"the",
"most",
"number",
"of",
"movies",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "first_name"
},
{
"id": 3,
"type": "table",
"value": "film_actor"
},
{
"id": 1,
"type": "column",
"value": "last_name"
},
{
"id": 6,
"type": "column",
"value": "actor_id"
},
{
"id": 5,
"type": "column",
"value": "film_id"
},
{
"id": 4,
"type": "table",
"value": "actor"
},
{
"id": 2,
"type": "column",
"value": "num"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
12
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O"
] |
1,763
|
bike_share_1
|
bird:train.json:9020
|
List the name of stations that were installed from 8/5/2013 to 12/31/2013. Indicate their installation date and city name.
|
SELECT name, installation_date, city FROM station WHERE (SUBSTR(CAST(installation_date AS TEXT), 1, INSTR(installation_date, '/') - 1) = '5' AND SUBSTR(CAST(installation_date AS TEXT), INSTR(installation_date, '/') + 1, -6) >= '8' AND SUBSTR(CAST(installation_date AS TEXT), -4) = '2013') OR (SUBSTR(CAST(installation_date AS TEXT), 1, INSTR(installation_date, '/') - 1) IN ( '6', '7', '8', '9', '10', '11', '12' ) AND SUBSTR(CAST(installation_date AS TEXT), -4) = '2013')
|
[
"List",
"the",
"name",
"of",
"stations",
"that",
"were",
"installed",
"from",
"8/5/2013",
"to",
"12/31/2013",
".",
"Indicate",
"their",
"installation",
"date",
"and",
"city",
"name",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "installation_date"
},
{
"id": 0,
"type": "table",
"value": "station"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "column",
"value": "city"
},
{
"id": 6,
"type": "value",
"value": "2013"
},
{
"id": 10,
"type": "value",
"value": "10"
},
{
"id": 11,
"type": "value",
"value": "11"
},
{
"id": 12,
"type": "value",
"value": "12"
},
{
"id": 14,
"type": "value",
"value": "-6"
},
{
"id": 15,
"type": "value",
"value": "-4"
},
{
"id": 4,
"type": "value",
"value": "5"
},
{
"id": 5,
"type": "value",
"value": "8"
},
{
"id": 7,
"type": "value",
"value": "6"
},
{
"id": 8,
"type": "value",
"value": "7"
},
{
"id": 9,
"type": "value",
"value": "9"
},
{
"id": 13,
"type": "value",
"value": "1"
},
{
"id": 16,
"type": "value",
"value": "/"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
15,
16
]
},
{
"entity_id": 3,
"token_idxs": [
18
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
9
]
},
{
"entity_id": 7,
"token_idxs": []
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{
"entity_id": 8,
"token_idxs": []
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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",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O"
] |
1,764
|
movie_3
|
bird:train.json:9364
|
Compute the total payment made by Sarah Lewis for film rentals so far.
|
SELECT SUM(T3.amount) FROM rental AS T1 INNER JOIN customer AS T2 ON T1.customer_id = T2.customer_id INNER JOIN payment AS T3 ON T1.rental_id = T3.rental_id WHERE T2.first_name = 'SARAH' AND T2.last_name = 'LEWIS'
|
[
"Compute",
"the",
"total",
"payment",
"made",
"by",
"Sarah",
"Lewis",
"for",
"film",
"rentals",
"so",
"far",
"."
] |
[
{
"id": 9,
"type": "column",
"value": "customer_id"
},
{
"id": 5,
"type": "column",
"value": "first_name"
},
{
"id": 4,
"type": "column",
"value": "rental_id"
},
{
"id": 7,
"type": "column",
"value": "last_name"
},
{
"id": 3,
"type": "table",
"value": "customer"
},
{
"id": 0,
"type": "table",
"value": "payment"
},
{
"id": 1,
"type": "column",
"value": "amount"
},
{
"id": 2,
"type": "table",
"value": "rental"
},
{
"id": 6,
"type": "value",
"value": "SARAH"
},
{
"id": 8,
"type": "value",
"value": "LEWIS"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
6
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
7
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"B-VALUE",
"O",
"O",
"B-TABLE",
"O",
"O",
"O"
] |
1,765
|
flight_1
|
spider:train_spider.json:402
|
What is the average distance and price for all flights from LA?
|
SELECT avg(distance) , avg(price) FROM Flight WHERE origin = "Los Angeles"
|
[
"What",
"is",
"the",
"average",
"distance",
"and",
"price",
"for",
"all",
"flights",
"from",
"LA",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "Los Angeles"
},
{
"id": 3,
"type": "column",
"value": "distance"
},
{
"id": 0,
"type": "table",
"value": "flight"
},
{
"id": 1,
"type": "column",
"value": "origin"
},
{
"id": 4,
"type": "column",
"value": "price"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O"
] |
1,766
|
products_gen_characteristics
|
spider:train_spider.json:5528
|
What are the names of products with category "Spices"?
|
SELECT product_name FROM products WHERE product_category_code = "Spices"
|
[
"What",
"are",
"the",
"names",
"of",
"products",
"with",
"category",
"\"",
"Spices",
"\"",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "product_category_code"
},
{
"id": 1,
"type": "column",
"value": "product_name"
},
{
"id": 0,
"type": "table",
"value": "products"
},
{
"id": 3,
"type": "column",
"value": "Spices"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6,
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": []
},
{
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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O"
] |
1,767
|
company_1
|
spider:train_spider.json:2136
|
Find the number of employees of each gender whose salary is lower than 50000.
|
SELECT count(*) , sex FROM employee WHERE salary < 50000 GROUP BY sex
|
[
"Find",
"the",
"number",
"of",
"employees",
"of",
"each",
"gender",
"whose",
"salary",
"is",
"lower",
"than",
"50000",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "employee"
},
{
"id": 2,
"type": "column",
"value": "salary"
},
{
"id": 3,
"type": "value",
"value": "50000"
},
{
"id": 1,
"type": "column",
"value": "sex"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
1,768
|
aircraft
|
spider:train_spider.json:4832
|
What are the names of all aicrafts that have never won any match?
|
SELECT Aircraft FROM aircraft WHERE Aircraft_ID NOT IN (SELECT Winning_Aircraft FROM MATCH)
|
[
"What",
"are",
"the",
"names",
"of",
"all",
"aicrafts",
"that",
"have",
"never",
"won",
"any",
"match",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "winning_aircraft"
},
{
"id": 2,
"type": "column",
"value": "aircraft_id"
},
{
"id": 0,
"type": "table",
"value": "aircraft"
},
{
"id": 1,
"type": "column",
"value": "aircraft"
},
{
"id": 3,
"type": "table",
"value": "match"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
1,769
|
superhero
|
bird:dev.json:837
|
Give the hero ID of superhero with the lowest attribute value.
|
SELECT hero_id FROM hero_attribute WHERE attribute_value = ( SELECT MIN(attribute_value) FROM hero_attribute )
|
[
"Give",
"the",
"hero",
"ID",
"of",
"superhero",
"with",
"the",
"lowest",
"attribute",
"value",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "attribute_value"
},
{
"id": 0,
"type": "table",
"value": "hero_attribute"
},
{
"id": 1,
"type": "column",
"value": "hero_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
"token_idxs": [
2,
3
]
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O"
] |
1,770
|
bike_share_1
|
bird:train.json:9070
|
When was the bike station from which the bike was borrowed on trip ID4069 installed?
|
SELECT T2.installation_date FROM trip AS T1 INNER JOIN station AS T2 ON T2.name = T1.start_station_name WHERE T1.id = 4069
|
[
"When",
"was",
"the",
"bike",
"station",
"from",
"which",
"the",
"bike",
"was",
"borrowed",
"on",
"trip",
"ID4069",
"installed",
"?"
] |
[
{
"id": 6,
"type": "column",
"value": "start_station_name"
},
{
"id": 0,
"type": "column",
"value": "installation_date"
},
{
"id": 2,
"type": "table",
"value": "station"
},
{
"id": 1,
"type": "table",
"value": "trip"
},
{
"id": 4,
"type": "value",
"value": "4069"
},
{
"id": 5,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
14
]
},
{
"entity_id": 1,
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12
]
},
{
"entity_id": 2,
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4
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
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13
]
},
{
"entity_id": 5,
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},
{
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},
{
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},
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},
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},
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},
{
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},
{
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},
{
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},
{
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"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-VALUE",
"B-COLUMN",
"O"
] |
1,772
|
retail_world
|
bird:train.json:6352
|
For the orders of Customer "WHITC", what is the percentage of the orders were fulfilled with shipper company "United Package"?
|
SELECT CAST(COUNT(CASE WHEN T2.CompanyName = 'United Package' THEN 1 ELSE NULL END) AS REAL) * 100 / COUNT(T1.OrderID) FROM Orders AS T1 INNER JOIN Shippers AS T2 ON T1.ShipVia = T2.ShipperID WHERE T1.CustomerID = 'WHITC'
|
[
"For",
"the",
"orders",
"of",
"Customer",
"\"",
"WHITC",
"\"",
",",
"what",
"is",
"the",
"percentage",
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"the",
"orders",
"were",
"fulfilled",
"with",
"shipper",
"company",
"\"",
"United",
"Package",
"\"",
"?"
] |
[
{
"id": 10,
"type": "value",
"value": "United Package"
},
{
"id": 9,
"type": "column",
"value": "companyname"
},
{
"id": 2,
"type": "column",
"value": "customerid"
},
{
"id": 5,
"type": "column",
"value": "shipperid"
},
{
"id": 1,
"type": "table",
"value": "shippers"
},
{
"id": 4,
"type": "column",
"value": "shipvia"
},
{
"id": 7,
"type": "column",
"value": "orderid"
},
{
"id": 0,
"type": "table",
"value": "orders"
},
{
"id": 3,
"type": "value",
"value": "WHITC"
},
{
"id": 6,
"type": "value",
"value": "100"
},
{
"id": 8,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
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19
]
},
{
"entity_id": 2,
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4
]
},
{
"entity_id": 3,
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6
]
},
{
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},
{
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{
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},
{
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15
]
},
{
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]
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{
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22,
23
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},
{
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"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O"
] |
1,773
|
cs_semester
|
bird:train.json:932
|
List the capability of research postgraduate students with an intellegence level of 4 and above.
|
SELECT T1.capability FROM RA AS T1 INNER JOIN student AS T2 ON T1.student_id = T2.student_id WHERE T2.type = 'RPG' AND T2.intelligence >= 4
|
[
"List",
"the",
"capability",
"of",
"research",
"postgraduate",
"students",
"with",
"an",
"intellegence",
"level",
"of",
"4",
"and",
"above",
"."
] |
[
{
"id": 6,
"type": "column",
"value": "intelligence"
},
{
"id": 0,
"type": "column",
"value": "capability"
},
{
"id": 3,
"type": "column",
"value": "student_id"
},
{
"id": 2,
"type": "table",
"value": "student"
},
{
"id": 4,
"type": "column",
"value": "type"
},
{
"id": 5,
"type": "value",
"value": "RPG"
},
{
"id": 1,
"type": "table",
"value": "ra"
},
{
"id": 7,
"type": "value",
"value": "4"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
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},
{
"entity_id": 5,
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},
{
"entity_id": 6,
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},
{
"entity_id": 7,
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]
},
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},
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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",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O",
"O"
] |
1,774
|
loan_1
|
spider:train_spider.json:3082
|
Find the average credit score of the customers who have some loan.
|
SELECT avg(credit_score) FROM customer WHERE cust_id IN (SELECT cust_id FROM loan)
|
[
"Find",
"the",
"average",
"credit",
"score",
"of",
"the",
"customers",
"who",
"have",
"some",
"loan",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "credit_score"
},
{
"id": 0,
"type": "table",
"value": "customer"
},
{
"id": 1,
"type": "column",
"value": "cust_id"
},
{
"id": 3,
"type": "table",
"value": "loan"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
3,
4
]
},
{
"entity_id": 3,
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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",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
1,775
|
university_basketball
|
spider:train_spider.json:1006
|
What are the schools that were either founded before 1850 or are public?
|
SELECT school FROM university WHERE founded > 1850 OR affiliation = 'Public'
|
[
"What",
"are",
"the",
"schools",
"that",
"were",
"either",
"founded",
"before",
"1850",
"or",
"are",
"public",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "affiliation"
},
{
"id": 0,
"type": "table",
"value": "university"
},
{
"id": 2,
"type": "column",
"value": "founded"
},
{
"id": 1,
"type": "column",
"value": "school"
},
{
"id": 5,
"type": "value",
"value": "Public"
},
{
"id": 3,
"type": "value",
"value": "1850"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
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3
]
},
{
"entity_id": 2,
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7
]
},
{
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9
]
},
{
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},
{
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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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},
{
"entity_id": 10,
"token_idxs": []
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{
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"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"B-VALUE",
"O"
] |
1,777
|
cookbook
|
bird:train.json:8878
|
Which recipe in the database contains the most total fat? Give its title.
|
SELECT T1.title FROM Recipe AS T1 INNER JOIN Nutrition AS T2 ON T1.recipe_id = T2.recipe_id ORDER BY T2.total_fat DESC LIMIT 1
|
[
"Which",
"recipe",
"in",
"the",
"database",
"contains",
"the",
"most",
"total",
"fat",
"?",
"Give",
"its",
"title",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "nutrition"
},
{
"id": 3,
"type": "column",
"value": "total_fat"
},
{
"id": 4,
"type": "column",
"value": "recipe_id"
},
{
"id": 1,
"type": "table",
"value": "recipe"
},
{
"id": 0,
"type": "column",
"value": "title"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
13
]
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
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",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
1,778
|
college_completion
|
bird:train.json:3685
|
What is the total male graduates in 2012 in the state whereby the institute with the highest average amount of student aid going to undergraduate recipients is located?
|
SELECT COUNT(T2.grad_cohort) FROM institution_details AS T1 INNER JOIN state_sector_grads AS T2 ON T1.state = T2.state WHERE T2.year = 2012 AND T2.gender = 'M' ORDER BY T1.aid_value DESC LIMIT 1
|
[
"What",
"is",
"the",
"total",
"male",
"graduates",
"in",
"2012",
"in",
"the",
"state",
"whereby",
"the",
"institute",
"with",
"the",
"highest",
"average",
"amount",
"of",
"student",
"aid",
"going",
"to",
"undergraduate",
"recipients",
"is",
"located",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "institution_details"
},
{
"id": 1,
"type": "table",
"value": "state_sector_grads"
},
{
"id": 3,
"type": "column",
"value": "grad_cohort"
},
{
"id": 2,
"type": "column",
"value": "aid_value"
},
{
"id": 7,
"type": "column",
"value": "gender"
},
{
"id": 4,
"type": "column",
"value": "state"
},
{
"id": 5,
"type": "column",
"value": "year"
},
{
"id": 6,
"type": "value",
"value": "2012"
},
{
"id": 8,
"type": "value",
"value": "M"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
13
]
},
{
"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": [
7
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
1,779
|
video_games
|
bird:train.json:3484
|
In which year did the record ID 19 with game publisher ID 6657 released?
|
SELECT T.release_year FROM game_platform AS T WHERE T.game_publisher_id = 6657 AND T.id = 19
|
[
"In",
"which",
"year",
"did",
"the",
"record",
"ID",
"19",
"with",
"game",
"publisher",
"ID",
"6657",
"released",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "game_publisher_id"
},
{
"id": 0,
"type": "table",
"value": "game_platform"
},
{
"id": 1,
"type": "column",
"value": "release_year"
},
{
"id": 3,
"type": "value",
"value": "6657"
},
{
"id": 4,
"type": "column",
"value": "id"
},
{
"id": 5,
"type": "value",
"value": "19"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
13
]
},
{
"entity_id": 2,
"token_idxs": [
9,
10,
11
]
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
"token_idxs": [
7
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"B-VALUE",
"B-COLUMN",
"O"
] |
1,780
|
college_2
|
spider:train_spider.json:1325
|
How many classrooms are not in Lamberton?
|
SELECT count(*) FROM classroom WHERE building != 'Lamberton'
|
[
"How",
"many",
"classrooms",
"are",
"not",
"in",
"Lamberton",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "classroom"
},
{
"id": 2,
"type": "value",
"value": "Lamberton"
},
{
"id": 1,
"type": "column",
"value": "building"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
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},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
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},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
1,781
|
mondial_geo
|
bird:train.json:8225
|
What is the full name of the country with 100% Africans?
|
SELECT T1.Name FROM ethnicGroup AS T1 INNER JOIN country AS T2 ON T1.Country = T2.Code WHERE T1.Percentage = 100 AND T1.Name = 'African'
|
[
"What",
"is",
"the",
"full",
"name",
"of",
"the",
"country",
"with",
"100",
"%",
"Africans",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "ethnicgroup"
},
{
"id": 5,
"type": "column",
"value": "percentage"
},
{
"id": 2,
"type": "table",
"value": "country"
},
{
"id": 3,
"type": "column",
"value": "country"
},
{
"id": 7,
"type": "value",
"value": "African"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "column",
"value": "code"
},
{
"id": 6,
"type": "value",
"value": "100"
}
] |
[
{
"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": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
9
]
},
{
"entity_id": 7,
"token_idxs": [
11
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
1,782
|
city_record
|
spider:train_spider.json:6271
|
What is the match id of the competition called "1994 FIFA World Cup qualification"?
|
SELECT match_id FROM MATCH WHERE competition = "1994 FIFA World Cup qualification"
|
[
"What",
"is",
"the",
"match",
"i",
"d",
"of",
"the",
"competition",
"called",
"\"",
"1994",
"FIFA",
"World",
"Cup",
"qualification",
"\"",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "1994 FIFA World Cup qualification"
},
{
"id": 2,
"type": "column",
"value": "competition"
},
{
"id": 1,
"type": "column",
"value": "match_id"
},
{
"id": 0,
"type": "table",
"value": "match"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
4,
5
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
11,
12,
13,
14,
15
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O"
] |
1,783
|
wine_1
|
spider:train_spider.json:6569
|
Find the distinct winery of wines having price between 50 and 100.
|
SELECT DISTINCT Winery FROM WINE WHERE Price BETWEEN 50 AND 100
|
[
"Find",
"the",
"distinct",
"winery",
"of",
"wines",
"having",
"price",
"between",
"50",
"and",
"100",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "winery"
},
{
"id": 2,
"type": "column",
"value": "price"
},
{
"id": 0,
"type": "table",
"value": "wine"
},
{
"id": 4,
"type": "value",
"value": "100"
},
{
"id": 3,
"type": "value",
"value": "50"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": [
11
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
1,784
|
storm_record
|
spider:train_spider.json:2730
|
Find the names of the regions which were affected by the storm that killed the greatest number of people.
|
SELECT T2.region_name FROM affected_region AS T1 JOIN region AS T2 ON T1.region_id = T2.region_id JOIN storm AS T3 ON T1.storm_id = T3.storm_id ORDER BY T3.Number_Deaths DESC LIMIT 1
|
[
"Find",
"the",
"names",
"of",
"the",
"regions",
"which",
"were",
"affected",
"by",
"the",
"storm",
"that",
"killed",
"the",
"greatest",
"number",
"of",
"people",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "affected_region"
},
{
"id": 2,
"type": "column",
"value": "number_deaths"
},
{
"id": 0,
"type": "column",
"value": "region_name"
},
{
"id": 6,
"type": "column",
"value": "region_id"
},
{
"id": 5,
"type": "column",
"value": "storm_id"
},
{
"id": 4,
"type": "table",
"value": "region"
},
{
"id": 1,
"type": "table",
"value": "storm"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
11
]
},
{
"entity_id": 2,
"token_idxs": [
16
]
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": [
5
]
},
{
"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": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O"
] |
1,785
|
video_games
|
bird:train.json:3337
|
Tell the genre of the game "Resident Evil: Revelations".
|
SELECT T2.genre_name FROM game AS T1 INNER JOIN genre AS T2 ON T1.genre_id = T2.id WHERE T1.game_name = 'Resident Evil: Revelations'
|
[
"Tell",
"the",
"genre",
"of",
"the",
"game",
"\"",
"Resident",
"Evil",
":",
"Revelations",
"\"",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "Resident Evil: Revelations"
},
{
"id": 0,
"type": "column",
"value": "genre_name"
},
{
"id": 3,
"type": "column",
"value": "game_name"
},
{
"id": 5,
"type": "column",
"value": "genre_id"
},
{
"id": 2,
"type": "table",
"value": "genre"
},
{
"id": 1,
"type": "table",
"value": "game"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
7,
8,
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",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
1,786
|
synthea
|
bird:train.json:1368
|
Please give the full names of all the patients who had been prescribed with Acetaminophen.
|
SELECT DISTINCT T1.first, T1.last FROM patients AS T1 INNER JOIN medications AS T2 ON T1.patient = T2.PATIENT WHERE T2.description LIKE 'Acetaminophen%'
|
[
"Please",
"give",
"the",
"full",
"names",
"of",
"all",
"the",
"patients",
"who",
"had",
"been",
"prescribed",
"with",
"Acetaminophen",
"."
] |
[
{
"id": 5,
"type": "value",
"value": "Acetaminophen%"
},
{
"id": 3,
"type": "table",
"value": "medications"
},
{
"id": 4,
"type": "column",
"value": "description"
},
{
"id": 2,
"type": "table",
"value": "patients"
},
{
"id": 6,
"type": "column",
"value": "patient"
},
{
"id": 0,
"type": "column",
"value": "first"
},
{
"id": 1,
"type": "column",
"value": "last"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
0
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
14
]
},
{
"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": []
}
] |
[
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
1,787
|
store_product
|
spider:train_spider.json:4933
|
What are the products with the maximum page size eqal to A4 or a pages per minute color less than 5?
|
SELECT product FROM product WHERE max_page_size = "A4" OR pages_per_minute_color < 5
|
[
"What",
"are",
"the",
"products",
"with",
"the",
"maximum",
"page",
"size",
"eqal",
"to",
"A4",
"or",
"a",
"pages",
"per",
"minute",
"color",
"less",
"than",
"5",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "pages_per_minute_color"
},
{
"id": 2,
"type": "column",
"value": "max_page_size"
},
{
"id": 0,
"type": "table",
"value": "product"
},
{
"id": 1,
"type": "column",
"value": "product"
},
{
"id": 3,
"type": "column",
"value": "A4"
},
{
"id": 5,
"type": "value",
"value": "5"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
7,
8
]
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": [
14,
15,
16,
17
]
},
{
"entity_id": 5,
"token_idxs": [
20
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
1,788
|
financial
|
bird:dev.json:192
|
What is the average amount of loan which are still on running contract with statement issuance after each transaction?
|
SELECT AVG(T2.amount) FROM account AS T1 INNER JOIN loan AS T2 ON T1.account_id = T2.account_id WHERE T2.status IN ('C', 'D') AND T1.frequency = 'POPLATEK PO OBRATU'
|
[
"What",
"is",
"the",
"average",
"amount",
"of",
"loan",
"which",
"are",
"still",
"on",
"running",
"contract",
"with",
"statement",
"issuance",
"after",
"each",
"transaction",
"?"
] |
[
{
"id": 8,
"type": "value",
"value": "POPLATEK PO OBRATU"
},
{
"id": 3,
"type": "column",
"value": "account_id"
},
{
"id": 7,
"type": "column",
"value": "frequency"
},
{
"id": 0,
"type": "table",
"value": "account"
},
{
"id": 2,
"type": "column",
"value": "amount"
},
{
"id": 4,
"type": "column",
"value": "status"
},
{
"id": 1,
"type": "table",
"value": "loan"
},
{
"id": 5,
"type": "value",
"value": "C"
},
{
"id": 6,
"type": "value",
"value": "D"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
1,789
|
car_retails
|
bird:train.json:1547
|
What was the total price of the products shipped to Rovelli Gifts Distributors Ltd. between 1/1/2003 and 12/31/2003?
|
SELECT T3.priceEach * T3.quantityOrdered FROM customers AS T1 INNER JOIN orders AS T2 ON T1.customerNumber = T2.customerNumber INNER JOIN orderdetails AS T3 ON T2.orderNumber = T3.orderNumber WHERE T1.customerName = 'Rovelli Gifts' AND T2.status = 'Shipped' AND STRFTIME('%Y', T2.shippedDate) = '2003'
|
[
"What",
"was",
"the",
"total",
"price",
"of",
"the",
"products",
"shipped",
"to",
"Rovelli",
"Gifts",
"Distributors",
"Ltd.",
"between",
"1/1/2003",
"and",
"12/31/2003",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "quantityordered"
},
{
"id": 11,
"type": "column",
"value": "customernumber"
},
{
"id": 7,
"type": "value",
"value": "Rovelli Gifts"
},
{
"id": 0,
"type": "table",
"value": "orderdetails"
},
{
"id": 6,
"type": "column",
"value": "customername"
},
{
"id": 5,
"type": "column",
"value": "ordernumber"
},
{
"id": 13,
"type": "column",
"value": "shippeddate"
},
{
"id": 1,
"type": "column",
"value": "priceeach"
},
{
"id": 3,
"type": "table",
"value": "customers"
},
{
"id": 9,
"type": "value",
"value": "Shipped"
},
{
"id": 4,
"type": "table",
"value": "orders"
},
{
"id": 8,
"type": "column",
"value": "status"
},
{
"id": 10,
"type": "value",
"value": "2003"
},
{
"id": 12,
"type": "value",
"value": "%Y"
}
] |
[
{
"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,
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10,
11
]
},
{
"entity_id": 8,
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},
{
"entity_id": 9,
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8
]
},
{
"entity_id": 10,
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15
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O"
] |
1,791
|
regional_sales
|
bird:train.json:2584
|
Provide all the orders from WARE-NMK1003. Name the product and sales team for each of these order.
|
SELECT DISTINCT T1.`Product Name`, T3.`Sales Team` FROM Products AS T1 INNER JOIN `Sales Orders` AS T2 ON T2._ProductID = T1.ProductID INNER JOIN `Sales Team` AS T3 ON T3.SalesTeamID = T2._SalesTeamID WHERE T2.WarehouseCode = 'WARE-NMK1003'
|
[
"Provide",
"all",
"the",
"orders",
"from",
"WARE",
"-",
"NMK1003",
".",
"Name",
"the",
"product",
"and",
"sales",
"team",
"for",
"each",
"of",
"these",
"order",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "warehousecode"
},
{
"id": 0,
"type": "column",
"value": "Product Name"
},
{
"id": 4,
"type": "value",
"value": "WARE-NMK1003"
},
{
"id": 6,
"type": "table",
"value": "Sales Orders"
},
{
"id": 8,
"type": "column",
"value": "_salesteamid"
},
{
"id": 7,
"type": "column",
"value": "salesteamid"
},
{
"id": 1,
"type": "column",
"value": "Sales Team"
},
{
"id": 2,
"type": "table",
"value": "Sales Team"
},
{
"id": 9,
"type": "column",
"value": "_productid"
},
{
"id": 10,
"type": "column",
"value": "productid"
},
{
"id": 5,
"type": "table",
"value": "products"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
12
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
13,
14
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
5,
6,
7
]
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
"token_idxs": [
1,
2,
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",
"B-TABLE",
"I-TABLE",
"I-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
1,792
|
chinook_1
|
spider:train_spider.json:814
|
Find the full names of employees living in the city of Calgary.
|
SELECT FirstName , LastName FROM EMPLOYEE WHERE City = "Calgary"
|
[
"Find",
"the",
"full",
"names",
"of",
"employees",
"living",
"in",
"the",
"city",
"of",
"Calgary",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "firstname"
},
{
"id": 0,
"type": "table",
"value": "employee"
},
{
"id": 2,
"type": "column",
"value": "lastname"
},
{
"id": 4,
"type": "column",
"value": "Calgary"
},
{
"id": 3,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": [
11
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O"
] |
1,793
|
culture_company
|
spider:train_spider.json:6963
|
Count the number of book clubs.
|
SELECT count(*) FROM book_club
|
[
"Count",
"the",
"number",
"of",
"book",
"clubs",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "book_club"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4,
5
]
},
{
"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",
"I-TABLE",
"O"
] |
1,794
|
toxicology
|
bird:dev.json:297
|
Among the atoms that contain element carbon, which one does not contain compound carcinogenic?
|
SELECT T1.atom_id FROM atom AS T1 INNER JOIN molecule AS T2 ON T1.molecule_id = T2.molecule_id WHERE T1.element = 'c' AND T2.label = '-'
|
[
"Among",
"the",
"atoms",
"that",
"contain",
"element",
"carbon",
",",
"which",
"one",
"does",
"not",
"contain",
"compound",
"carcinogenic",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "molecule_id"
},
{
"id": 2,
"type": "table",
"value": "molecule"
},
{
"id": 0,
"type": "column",
"value": "atom_id"
},
{
"id": 4,
"type": "column",
"value": "element"
},
{
"id": 6,
"type": "column",
"value": "label"
},
{
"id": 1,
"type": "table",
"value": "atom"
},
{
"id": 5,
"type": "value",
"value": "c"
},
{
"id": 7,
"type": "value",
"value": "-"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
5
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
1,795
|
insurance_policies
|
spider:train_spider.json:3896
|
Find the total claimed amount of all the claims.
|
SELECT sum(Amount_Claimed) FROM Claims
|
[
"Find",
"the",
"total",
"claimed",
"amount",
"of",
"all",
"the",
"claims",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "amount_claimed"
},
{
"id": 0,
"type": "table",
"value": "claims"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
2,
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
1,797
|
toxicology
|
bird:dev.json:330
|
Calculate the percentage of carcinogenic molecules with triple bonded Hidrogen atoms.
|
SELECT CAST(SUM(CASE WHEN T1.label = '+' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(DISTINCT T1.molecule_id) FROM molecule AS T1 INNER JOIN atom AS T2 ON T1.molecule_id = T2.molecule_id INNER JOIN bond AS T3 ON T1.molecule_id = T3.molecule_id WHERE T3.bond_type = '#' AND T2.element = 'h'
|
[
"Calculate",
"the",
"percentage",
"of",
"carcinogenic",
"molecules",
"with",
"triple",
"bonded",
"Hidrogen",
"atoms",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "molecule_id"
},
{
"id": 4,
"type": "column",
"value": "bond_type"
},
{
"id": 1,
"type": "table",
"value": "molecule"
},
{
"id": 6,
"type": "column",
"value": "element"
},
{
"id": 11,
"type": "column",
"value": "label"
},
{
"id": 0,
"type": "table",
"value": "bond"
},
{
"id": 2,
"type": "table",
"value": "atom"
},
{
"id": 8,
"type": "value",
"value": "100"
},
{
"id": 5,
"type": "value",
"value": "#"
},
{
"id": 7,
"type": "value",
"value": "h"
},
{
"id": 9,
"type": "value",
"value": "0"
},
{
"id": 10,
"type": "value",
"value": "1"
},
{
"id": 12,
"type": "value",
"value": "+"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"O"
] |
1,798
|
browser_web
|
spider:train_spider.json:1832
|
What is the name of the browser that became compatible with the accelerator 'CProxy' after year 1998 ?
|
SELECT T1.name FROM browser AS T1 JOIN accelerator_compatible_browser AS T2 ON T1.id = T2.browser_id JOIN web_client_accelerator AS T3 ON T2.accelerator_id = T3.id WHERE T3.name = 'CProxy' AND T2.compatible_since_year > 1998
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"browser",
"that",
"became",
"compatible",
"with",
"the",
"accelerator",
"'",
"CProxy",
"'",
"after",
"year",
"1998",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "accelerator_compatible_browser"
},
{
"id": 1,
"type": "table",
"value": "web_client_accelerator"
},
{
"id": 7,
"type": "column",
"value": "compatible_since_year"
},
{
"id": 4,
"type": "column",
"value": "accelerator_id"
},
{
"id": 9,
"type": "column",
"value": "browser_id"
},
{
"id": 2,
"type": "table",
"value": "browser"
},
{
"id": 6,
"type": "value",
"value": "CProxy"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 8,
"type": "value",
"value": "1998"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
13,
15,
16
]
},
{
"entity_id": 4,
"token_idxs": [
12
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
14
]
},
{
"entity_id": 7,
"token_idxs": [
9
]
},
{
"entity_id": 8,
"token_idxs": [
18
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"B-VALUE",
"B-TABLE",
"I-TABLE",
"O",
"B-VALUE",
"O"
] |
1,799
|
retail_complains
|
bird:train.json:353
|
Pick 5 clients with 0 priority and write down their last name.
|
SELECT T1.last FROM client AS T1 INNER JOIN callcenterlogs AS T2 ON T1.client_id = T2.`rand client` WHERE T2.priority = 0 LIMIT 5
|
[
"Pick",
"5",
"clients",
"with",
"0",
"priority",
"and",
"write",
"down",
"their",
"last",
"name",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "callcenterlogs"
},
{
"id": 6,
"type": "column",
"value": "rand client"
},
{
"id": 5,
"type": "column",
"value": "client_id"
},
{
"id": 3,
"type": "column",
"value": "priority"
},
{
"id": 1,
"type": "table",
"value": "client"
},
{
"id": 0,
"type": "column",
"value": "last"
},
{
"id": 4,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
"entity_id": 4,
"token_idxs": [
4
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
1
]
},
{
"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",
"B-TABLE",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
1,800
|
college_3
|
spider:train_spider.json:4678
|
What is the least common faculty rank?
|
SELECT Rank FROM FACULTY GROUP BY Rank ORDER BY count(*) ASC LIMIT 1
|
[
"What",
"is",
"the",
"least",
"common",
"faculty",
"rank",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "faculty"
},
{
"id": 1,
"type": "column",
"value": "rank"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"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",
"B-TABLE",
"B-COLUMN",
"O"
] |
1,802
|
talkingdata
|
bird:train.json:1082
|
Please list the ages of all the users who use a Galaxy Note 2.
|
SELECT T2.age FROM phone_brand_device_model2 AS T1 INNER JOIN gender_age AS T2 ON T2.device_id = T1.device_id WHERE T1.device_model = 'Galaxy Note 2'
|
[
"Please",
"list",
"the",
"ages",
"of",
"all",
"the",
"users",
"who",
"use",
"a",
"Galaxy",
"Note",
"2",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "phone_brand_device_model2"
},
{
"id": 4,
"type": "value",
"value": "Galaxy Note 2"
},
{
"id": 3,
"type": "column",
"value": "device_model"
},
{
"id": 2,
"type": "table",
"value": "gender_age"
},
{
"id": 5,
"type": "column",
"value": "device_id"
},
{
"id": 0,
"type": "column",
"value": "age"
}
] |
[
{
"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": [
11,
12,
13
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
1,803
|
hospital_1
|
spider:train_spider.json:3907
|
Which patients made more than one appointment? Tell me the name and phone number of these patients.
|
SELECT name , phone FROM appointment AS T1 JOIN patient AS T2 ON T1.patient = T2.ssn GROUP BY T1.patient HAVING count(*) > 1
|
[
"Which",
"patients",
"made",
"more",
"than",
"one",
"appointment",
"?",
"Tell",
"me",
"the",
"name",
"and",
"phone",
"number",
"of",
"these",
"patients",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "appointment"
},
{
"id": 0,
"type": "column",
"value": "patient"
},
{
"id": 4,
"type": "table",
"value": "patient"
},
{
"id": 2,
"type": "column",
"value": "phone"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 6,
"type": "column",
"value": "ssn"
},
{
"id": 5,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
11
]
},
{
"entity_id": 2,
"token_idxs": [
13
]
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": [
1
]
},
{
"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",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
1,804
|
works_cycles
|
bird:train.json:7134
|
How much do the works data saved in English and Arabic differ from one another?
|
SELECT SUM(CASE WHEN T1.Name = 'English' THEN 1 ELSE 0 END) - SUM(CASE WHEN T1.Name = 'Arabic' THEN 1 ELSE 0 END) FROM Culture AS T1 INNER JOIN ProductModelProductDescriptionCulture AS T2 ON T1.CultureID = T2.CultureID WHERE T1.Name = 'English' OR T1.Name = 'Arabic'
|
[
"How",
"much",
"do",
"the",
"works",
"data",
"saved",
"in",
"English",
"and",
"Arabic",
"differ",
"from",
"one",
"another",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "productmodelproductdescriptionculture"
},
{
"id": 2,
"type": "column",
"value": "cultureid"
},
{
"id": 0,
"type": "table",
"value": "culture"
},
{
"id": 4,
"type": "value",
"value": "English"
},
{
"id": 5,
"type": "value",
"value": "Arabic"
},
{
"id": 3,
"type": "column",
"value": "name"
},
{
"id": 6,
"type": "value",
"value": "0"
},
{
"id": 7,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
8
]
},
{
"entity_id": 5,
"token_idxs": [
10
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O"
] |
1,805
|
soccer_2016
|
bird:train.json:1935
|
How many times did the matches were held in MA Chidambaram Stadium from 5/9/2009 to 8/8/2011?
|
SELECT SUM(CASE WHEN Venue_Name = 'MA Chidambaram Stadium' THEN 1 ELSE 0 END) FROM `Match` AS T1 INNER JOIN Venue AS T2 ON T1.Venue_Id = T2.Venue_Id WHERE Match_Date BETWEEN '2009-05-09' AND '2011-08-08'
|
[
"How",
"many",
"times",
"did",
"the",
"matches",
"were",
"held",
"in",
"MA",
"Chidambaram",
"Stadium",
"from",
"5/9/2009",
"to",
"8/8/2011",
"?"
] |
[
{
"id": 9,
"type": "value",
"value": "MA Chidambaram Stadium"
},
{
"id": 2,
"type": "column",
"value": "match_date"
},
{
"id": 3,
"type": "value",
"value": "2009-05-09"
},
{
"id": 4,
"type": "value",
"value": "2011-08-08"
},
{
"id": 8,
"type": "column",
"value": "venue_name"
},
{
"id": 5,
"type": "column",
"value": "venue_id"
},
{
"id": 0,
"type": "table",
"value": "Match"
},
{
"id": 1,
"type": "table",
"value": "venue"
},
{
"id": 6,
"type": "value",
"value": "0"
},
{
"id": 7,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"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": [
9,
10,
11
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"O"
] |
1,806
|
headphone_store
|
bird:test.json:951
|
Find the name of the store which has the most headphones in stock. List the number of headphones as well.
|
SELECT t1.name , sum(t2.quantity) FROM store AS t1 JOIN stock AS t2 ON t1.store_id = t2.store_id GROUP BY t2.store_id ORDER BY sum(t2.quantity) DESC LIMIT 1
|
[
"Find",
"the",
"name",
"of",
"the",
"store",
"which",
"has",
"the",
"most",
"headphones",
"in",
"stock",
".",
"List",
"the",
"number",
"of",
"headphones",
"as",
"well",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "store_id"
},
{
"id": 4,
"type": "column",
"value": "quantity"
},
{
"id": 2,
"type": "table",
"value": "store"
},
{
"id": 3,
"type": "table",
"value": "stock"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
1,807
|
legislator
|
bird:train.json:4899
|
What is the official full name of the current legislator whose current official Facebook presence is "senjoniernst"?
|
SELECT T1.official_full_name FROM current AS T1 INNER JOIN `social-media` AS T2 ON T1.bioguide_id = T2.bioguide WHERE T2.facebook = 'senjoniernst'
|
[
"What",
"is",
"the",
"official",
"full",
"name",
"of",
"the",
"current",
"legislator",
"whose",
"current",
"official",
"Facebook",
"presence",
"is",
"\"",
"senjoniernst",
"\"",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "official_full_name"
},
{
"id": 2,
"type": "table",
"value": "social-media"
},
{
"id": 4,
"type": "value",
"value": "senjoniernst"
},
{
"id": 5,
"type": "column",
"value": "bioguide_id"
},
{
"id": 3,
"type": "column",
"value": "facebook"
},
{
"id": 6,
"type": "column",
"value": "bioguide"
},
{
"id": 1,
"type": "table",
"value": "current"
}
] |
[
{
"entity_id": 0,
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3,
4,
5
]
},
{
"entity_id": 1,
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]
},
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},
{
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13
]
},
{
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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": 14,
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},
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"entity_id": 15,
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},
{
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},
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
1,808
|
mondial_geo
|
bird:train.json:8318
|
What is the average inflation rate of the biggest continent?
|
SELECT AVG(T4.Inflation) FROM continent AS T1 INNER JOIN encompasses AS T2 ON T1.Name = T2.Continent INNER JOIN country AS T3 ON T3.Code = T2.Country INNER JOIN economy AS T4 ON T4.Country = T3.Code WHERE T1.Name = ( SELECT Name FROM continent ORDER BY Area DESC LIMIT 1 )
|
[
"What",
"is",
"the",
"average",
"inflation",
"rate",
"of",
"the",
"biggest",
"continent",
"?"
] |
[
{
"id": 7,
"type": "table",
"value": "encompasses"
},
{
"id": 2,
"type": "column",
"value": "inflation"
},
{
"id": 6,
"type": "table",
"value": "continent"
},
{
"id": 8,
"type": "column",
"value": "continent"
},
{
"id": 0,
"type": "table",
"value": "economy"
},
{
"id": 3,
"type": "table",
"value": "country"
},
{
"id": 4,
"type": "column",
"value": "country"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "column",
"value": "code"
},
{
"id": 9,
"type": "column",
"value": "area"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
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4
]
},
{
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},
{
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},
{
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},
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},
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},
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},
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},
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},
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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",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
1,809
|
shipping
|
bird:train.json:5657
|
Which headquarter's truck has the highest shipments in year 2016?
|
SELECT CASE WHEN T2.make = 'Peterbilt' THEN 'Texas (TX)' WHEN T2.make = 'Mack' THEN 'North Carolina (NC)' WHEN T2.make = 'Kenworth' THEN 'Washington (WA)' END AS "result" FROM shipment AS T1 INNER JOIN truck AS T2 ON T1.truck_id = T2.truck_id WHERE CAST(T1.ship_date AS DATE) = 2016 GROUP BY T2.make ORDER BY COUNT(T1.ship_id) DESC LIMIT 1
|
[
"Which",
"headquarter",
"'s",
"truck",
"has",
"the",
"highest",
"shipments",
"in",
"year",
"2016",
"?"
] |
[
{
"id": 8,
"type": "value",
"value": "North Carolina (NC)"
},
{
"id": 9,
"type": "value",
"value": "Washington (WA)"
},
{
"id": 7,
"type": "value",
"value": "Texas (TX)"
},
{
"id": 5,
"type": "column",
"value": "ship_date"
},
{
"id": 10,
"type": "value",
"value": "Peterbilt"
},
{
"id": 1,
"type": "table",
"value": "shipment"
},
{
"id": 4,
"type": "column",
"value": "truck_id"
},
{
"id": 12,
"type": "value",
"value": "Kenworth"
},
{
"id": 6,
"type": "column",
"value": "ship_id"
},
{
"id": 2,
"type": "table",
"value": "truck"
},
{
"id": 0,
"type": "column",
"value": "make"
},
{
"id": 3,
"type": "value",
"value": "2016"
},
{
"id": 11,
"type": "value",
"value": "Mack"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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7
]
},
{
"entity_id": 2,
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3
]
},
{
"entity_id": 3,
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]
},
{
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},
{
"entity_id": 5,
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},
{
"entity_id": 6,
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"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
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"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O"
] |
1,810
|
human_resources
|
bird:train.json:8955
|
Who is the highest paid employee in "Boston"? Give the full name.
|
SELECT T1.firstname, T1.lastname FROM employee AS T1 INNER JOIN location AS T2 ON T1.locationID = T2.locationID WHERE T2.locationcity = 'Boston' ORDER BY T1.salary DESC LIMIT 1
|
[
"Who",
"is",
"the",
"highest",
"paid",
"employee",
"in",
"\"",
"Boston",
"\"",
"?",
"Give",
"the",
"full",
"name",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "locationcity"
},
{
"id": 7,
"type": "column",
"value": "locationid"
},
{
"id": 0,
"type": "column",
"value": "firstname"
},
{
"id": 1,
"type": "column",
"value": "lastname"
},
{
"id": 2,
"type": "table",
"value": "employee"
},
{
"id": 3,
"type": "table",
"value": "location"
},
{
"id": 5,
"type": "value",
"value": "Boston"
},
{
"id": 6,
"type": "column",
"value": "salary"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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14
]
},
{
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5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
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},
{
"entity_id": 5,
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},
{
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},
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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": []
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
1,811
|
music_4
|
spider:train_spider.json:6146
|
What are the ages of all music artists?
|
SELECT Age FROM artist
|
[
"What",
"are",
"the",
"ages",
"of",
"all",
"music",
"artists",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "artist"
},
{
"id": 1,
"type": "column",
"value": "age"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
1,812
|
public_review_platform
|
bird:train.json:3991
|
Calculate difference between business that have the highest number of reviews and business that have the lowest number of reviews.
|
SELECT ( SELECT COUNT(business_id) FROM Reviews GROUP BY business_id ORDER BY COUNT(business_id) DESC LIMIT 1 ) - ( SELECT COUNT(business_id) FROM Reviews GROUP BY business_id ORDER BY COUNT(business_id) ASC LIMIT 1 ) AS DIFF
|
[
"Calculate",
"difference",
"between",
"business",
"that",
"have",
"the",
"highest",
"number",
"of",
"reviews",
"and",
"business",
"that",
"have",
"the",
"lowest",
"number",
"of",
"reviews",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "business_id"
},
{
"id": 0,
"type": "table",
"value": "reviews"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
19
]
},
{
"entity_id": 1,
"token_idxs": [
12
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
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"token_idxs": []
},
{
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"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
1,813
|
video_games
|
bird:train.json:3447
|
What is the total number of games sold in region ID 1?
|
SELECT SUM(T.num_sales * 100000) FROM region_sales AS T WHERE T.region_id = 1
|
[
"What",
"is",
"the",
"total",
"number",
"of",
"games",
"sold",
"in",
"region",
"ID",
"1",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "region_sales"
},
{
"id": 1,
"type": "column",
"value": "region_id"
},
{
"id": 3,
"type": "column",
"value": "num_sales"
},
{
"id": 4,
"type": "value",
"value": "100000"
},
{
"id": 2,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
9,
10
]
},
{
"entity_id": 2,
"token_idxs": [
11
]
},
{
"entity_id": 3,
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},
{
"entity_id": 4,
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},
{
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},
{
"entity_id": 6,
"token_idxs": []
},
{
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},
{
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},
{
"entity_id": 9,
"token_idxs": []
},
{
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},
{
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},
{
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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"O"
] |
1,814
|
chicago_crime
|
bird:train.json:8610
|
How many simple assaults happened on 2018/9/8?
|
SELECT SUM(CASE WHEN T2.secondary_description = 'SIMPLE' THEN 1 ELSE 0 END) FROM Crime AS T1 INNER JOIN IUCR AS T2 ON T1.iucr_no = T2.iucr_no WHERE T1.date LIKE '%9/8/2018%' AND T2.primary_description = 'ASSAULT'
|
[
"How",
"many",
"simple",
"assaults",
"happened",
"on",
"2018/9/8",
"?"
] |
[
{
"id": 9,
"type": "column",
"value": "secondary_description"
},
{
"id": 5,
"type": "column",
"value": "primary_description"
},
{
"id": 4,
"type": "value",
"value": "%9/8/2018%"
},
{
"id": 2,
"type": "column",
"value": "iucr_no"
},
{
"id": 6,
"type": "value",
"value": "ASSAULT"
},
{
"id": 10,
"type": "value",
"value": "SIMPLE"
},
{
"id": 0,
"type": "table",
"value": "crime"
},
{
"id": 1,
"type": "table",
"value": "iucr"
},
{
"id": 3,
"type": "column",
"value": "date"
},
{
"id": 7,
"type": "value",
"value": "0"
},
{
"id": 8,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
3
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},
{
"entity_id": 7,
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},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": [
2
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-VALUE",
"B-VALUE",
"O",
"O",
"O",
"O"
] |
1,815
|
cre_Drama_Workshop_Groups
|
spider:train_spider.json:5107
|
Find the marketing region description of China?
|
SELECT Marketing_Region_Descriptrion FROM Marketing_Regions WHERE Marketing_Region_Name = "China"
|
[
"Find",
"the",
"marketing",
"region",
"description",
"of",
"China",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "marketing_region_descriptrion"
},
{
"id": 2,
"type": "column",
"value": "marketing_region_name"
},
{
"id": 0,
"type": "table",
"value": "marketing_regions"
},
{
"id": 3,
"type": "column",
"value": "China"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"O",
"B-COLUMN",
"O"
] |
1,816
|
train_station
|
spider:train_spider.json:6607
|
Show all locations which don't have a train station with at least 15 platforms.
|
SELECT LOCATION FROM station EXCEPT SELECT LOCATION FROM station WHERE number_of_platforms >= 15
|
[
"Show",
"all",
"locations",
"which",
"do",
"n't",
"have",
"a",
"train",
"station",
"with",
"at",
"least",
"15",
"platforms",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "number_of_platforms"
},
{
"id": 1,
"type": "column",
"value": "location"
},
{
"id": 0,
"type": "table",
"value": "station"
},
{
"id": 3,
"type": "value",
"value": "15"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
14
]
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
1,817
|
college_2
|
spider:train_spider.json:1337
|
Count the number of students who have advisors.
|
SELECT count(DISTINCT s_id) FROM advisor
|
[
"Count",
"the",
"number",
"of",
"students",
"who",
"have",
"advisors",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "advisor"
},
{
"id": 1,
"type": "column",
"value": "s_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"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",
"B-TABLE",
"O"
] |
1,818
|
bakery_1
|
bird:test.json:1578
|
What are the ids and flavors of cakes, ordered by flavor?
|
SELECT id , flavor FROM goods WHERE food = "Cake" ORDER BY flavor
|
[
"What",
"are",
"the",
"ids",
"and",
"flavors",
"of",
"cakes",
",",
"ordered",
"by",
"flavor",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "flavor"
},
{
"id": 0,
"type": "table",
"value": "goods"
},
{
"id": 3,
"type": "column",
"value": "food"
},
{
"id": 4,
"type": "column",
"value": "Cake"
},
{
"id": 1,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
11
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
7
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
1,819
|
game_injury
|
spider:train_spider.json:1281
|
What are the ids, scores, and dates of the games which caused at least two injury accidents?
|
SELECT T1.id , T1.score , T1.date FROM game AS T1 JOIN injury_accident AS T2 ON T2.game_id = T1.id GROUP BY T1.id HAVING count(*) >= 2
|
[
"What",
"are",
"the",
"ids",
",",
"scores",
",",
"and",
"dates",
"of",
"the",
"games",
"which",
"caused",
"at",
"least",
"two",
"injury",
"accidents",
"?"
] |
[
{
"id": 4,
"type": "table",
"value": "injury_accident"
},
{
"id": 6,
"type": "column",
"value": "game_id"
},
{
"id": 1,
"type": "column",
"value": "score"
},
{
"id": 2,
"type": "column",
"value": "date"
},
{
"id": 3,
"type": "table",
"value": "game"
},
{
"id": 0,
"type": "column",
"value": "id"
},
{
"id": 5,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": [
17,
18
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O"
] |
1,820
|
language_corpus
|
bird:train.json:5804
|
How many times of repetition does the word "exemple" show in the Catalan language?
|
SELECT T2.occurrences FROM words AS T1 INNER JOIN langs_words AS T2 ON T1.wid = T2.wid WHERE T1.word = 'exemple' AND T2.lid = 1
|
[
"How",
"many",
"times",
"of",
"repetition",
"does",
"the",
"word",
"\"",
"exemple",
"\"",
"show",
"in",
"the",
"Catalan",
"language",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "occurrences"
},
{
"id": 2,
"type": "table",
"value": "langs_words"
},
{
"id": 5,
"type": "value",
"value": "exemple"
},
{
"id": 1,
"type": "table",
"value": "words"
},
{
"id": 4,
"type": "column",
"value": "word"
},
{
"id": 3,
"type": "column",
"value": "wid"
},
{
"id": 6,
"type": "column",
"value": "lid"
},
{
"id": 7,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
7
]
},
{
"entity_id": 5,
"token_idxs": [
9
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
1,821
|
college_2
|
spider:train_spider.json:1444
|
Find the names of instructors who didn't each any courses in any Spring semester.
|
SELECT name FROM instructor WHERE id NOT IN (SELECT id FROM teaches WHERE semester = 'Spring')
|
[
"Find",
"the",
"names",
"of",
"instructors",
"who",
"did",
"n't",
"each",
"any",
"courses",
"in",
"any",
"Spring",
"semester",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "instructor"
},
{
"id": 4,
"type": "column",
"value": "semester"
},
{
"id": 3,
"type": "table",
"value": "teaches"
},
{
"id": 5,
"type": "value",
"value": "Spring"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"entity_id": 5,
"token_idxs": [
13
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
1,822
|
college_1
|
spider:train_spider.json:3272
|
Which department has the most professors with a Ph.D.?
|
SELECT T2.dept_name , T1.dept_code FROM professor AS T1 JOIN department AS T2 ON T1.dept_code = T2.dept_code WHERE T1.prof_high_degree = 'Ph.D.' GROUP BY T1.dept_code ORDER BY count(*) DESC LIMIT 1
|
[
"Which",
"department",
"has",
"the",
"most",
"professors",
"with",
"a",
"Ph.D.",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "prof_high_degree"
},
{
"id": 3,
"type": "table",
"value": "department"
},
{
"id": 0,
"type": "column",
"value": "dept_code"
},
{
"id": 1,
"type": "column",
"value": "dept_name"
},
{
"id": 2,
"type": "table",
"value": "professor"
},
{
"id": 5,
"type": "value",
"value": "Ph.D."
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"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": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O"
] |
1,823
|
app_store
|
bird:train.json:2564
|
Name the Apps with a sentiment objectivity of 0.3 and include their number of installs.
|
SELECT DISTINCT T1.App, T1.Installs FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T2.Sentiment_Polarity = 0.3
|
[
"Name",
"the",
"Apps",
"with",
"a",
"sentiment",
"objectivity",
"of",
"0.3",
"and",
"include",
"their",
"number",
"of",
"installs",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "sentiment_polarity"
},
{
"id": 3,
"type": "table",
"value": "user_reviews"
},
{
"id": 2,
"type": "table",
"value": "playstore"
},
{
"id": 1,
"type": "column",
"value": "installs"
},
{
"id": 0,
"type": "column",
"value": "app"
},
{
"id": 5,
"type": "value",
"value": "0.3"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
14
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
5
]
},
{
"entity_id": 5,
"token_idxs": [
8
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
1,825
|
movie_1
|
spider:train_spider.json:2502
|
For each director, return the director's name together with the title of the movie they directed that received the highest rating among all of their movies, and the value of that rating. Ignore movies whose director is NULL.
|
SELECT T2.title , T1.stars , T2.director , max(T1.stars) FROM Rating AS T1 JOIN Movie AS T2 ON T1.mID = T2.mID WHERE director != "null" GROUP BY director
|
[
"For",
"each",
"director",
",",
"return",
"the",
"director",
"'s",
"name",
"together",
"with",
"the",
"title",
"of",
"the",
"movie",
"they",
"directed",
"that",
"received",
"the",
"highest",
"rating",
"among",
"all",
"of",
"their",
"movies",
",",
"and",
"the",
"value",
"of",
"that",
"rating",
".",
"Ignore",
"movies",
"whose",
"director",
"is",
"NULL",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "director"
},
{
"id": 3,
"type": "table",
"value": "rating"
},
{
"id": 1,
"type": "column",
"value": "title"
},
{
"id": 2,
"type": "column",
"value": "stars"
},
{
"id": 4,
"type": "table",
"value": "movie"
},
{
"id": 5,
"type": "column",
"value": "null"
},
{
"id": 6,
"type": "column",
"value": "mid"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
12
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
22
]
},
{
"entity_id": 4,
"token_idxs": [
15
]
},
{
"entity_id": 5,
"token_idxs": [
41
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
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{
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},
{
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},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
1,826
|
mental_health_survey
|
bird:train.json:4595
|
Tell the question ID for "Would you bring up a physical health issue with a potential employer in an interview?".
|
SELECT questionid FROM Question WHERE questiontext LIKE 'Would you bring up a physical health issue with a potential employer in an interview?'
|
[
"Tell",
"the",
"question",
"ID",
"for",
"\"",
"Would",
"you",
"bring",
"up",
"a",
"physical",
"health",
"issue",
"with",
"a",
"potential",
"employer",
"in",
"an",
"interview",
"?",
"\"",
"."
] |
[
{
"id": 3,
"type": "value",
"value": "Would you bring up a physical health issue with a potential employer in an interview?"
},
{
"id": 2,
"type": "column",
"value": "questiontext"
},
{
"id": 1,
"type": "column",
"value": "questionid"
},
{
"id": 0,
"type": "table",
"value": "question"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
1,828
|
books
|
bird:train.json:5999
|
What are the books published by "Harper Collins"?
|
SELECT T1.title FROM book AS T1 INNER JOIN publisher AS T2 ON T1.publisher_id = T2.publisher_id WHERE T2.publisher_name = 'Harper Collins'
|
[
"What",
"are",
"the",
"books",
"published",
"by",
"\"",
"Harper",
"Collins",
"\"",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "publisher_name"
},
{
"id": 4,
"type": "value",
"value": "Harper Collins"
},
{
"id": 5,
"type": "column",
"value": "publisher_id"
},
{
"id": 2,
"type": "table",
"value": "publisher"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 1,
"type": "table",
"value": "book"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
7,
8
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"B-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O"
] |
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