question_id
int64
0
16.1k
db_id
stringclasses
259 values
dber_id
stringlengths
15
29
question
stringlengths
16
325
SQL
stringlengths
18
1.25k
tokens
listlengths
4
62
entities
listlengths
0
21
entity_to_token
listlengths
20
20
dber_tags
listlengths
4
62
110
boat_1
bird:test.json:870
What are the ids of sailors who have not reserved a boat?
SELECT sid FROM Sailors EXCEPT SELECT sid FROM Reserves
[ "What", "are", "the", "ids", "of", "sailors", "who", "have", "not", "reserved", "a", "boat", "?" ]
[ { "id": 1, "type": "table", "value": "reserves" }, { "id": 0, "type": "table", "value": "sailors" }, { "id": 2, "type": "column", "value": "sid" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [ 9 ] }, { "entity_id": 2, "token_idxs": [ 3 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "B-TABLE", "O", "O", "O" ]
111
advertising_agencies
bird:test.json:2067
What is the agency id and details with most number of clients?
SELECT T1.agency_id , T1.agency_details FROM Agencies AS T1 JOIN Clients AS T2 ON T1.agency_id = T2.agency_id GROUP BY T1.agency_id ORDER BY count(*) DESC LIMIT 1
[ "What", "is", "the", "agency", "i", "d", "and", "details", "with", "most", "number", "of", "clients", "?" ]
[ { "id": 1, "type": "column", "value": "agency_details" }, { "id": 0, "type": "column", "value": "agency_id" }, { "id": 2, "type": "table", "value": "agencies" }, { "id": 3, "type": "table", "value": "clients" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [ 6, 7 ] }, { "entity_id": 2, "token_idxs": [ 3, 4 ] }, { "entity_id": 3, "token_idxs": [ 12 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-TABLE", "I-TABLE", "B-COLUMN", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-TABLE", "O" ]
112
donor
bird:train.json:3223
Is the donor who donated to school "d4af834b1d3fc8061e1ee1b3f1a77b85" a teacher?
SELECT T2.is_teacher_acct FROM projects AS T1 INNER JOIN donations AS T2 ON T1.projectid = T2.projectid WHERE T1.schoolid = 'd4af834b1d3fc8061e1ee1b3f1a77b85'
[ "Is", "the", "donor", "who", "donated", "to", "school", "\"", "d4af834b1d3fc8061e1ee1b3f1a77b85", "\"", "a", "teacher", "?" ]
[ { "id": 4, "type": "value", "value": "d4af834b1d3fc8061e1ee1b3f1a77b85" }, { "id": 0, "type": "column", "value": "is_teacher_acct" }, { "id": 2, "type": "table", "value": "donations" }, { "id": 5, "type": "column", "value": "projectid" }, { "id": 1, "type": "table", "value": "projects" }, { "id": 3, "type": "column", "value": "schoolid" } ]
[ { "entity_id": 0, "token_idxs": [ 11 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 4, 5 ] }, { "entity_id": 3, "token_idxs": [ 6 ] }, { "entity_id": 4, "token_idxs": [ 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", "O", "B-TABLE", "I-TABLE", "B-COLUMN", "O", "B-VALUE", "O", "O", "B-COLUMN", "O" ]
113
performance_attendance
spider:train_spider.json:1321
List the names of members who did not attend any performance.
SELECT Name FROM member WHERE Member_ID NOT IN (SELECT Member_ID FROM member_attendance)
[ "List", "the", "names", "of", "members", "who", "did", "not", "attend", "any", "performance", "." ]
[ { "id": 3, "type": "table", "value": "member_attendance" }, { "id": 2, "type": "column", "value": "member_id" }, { "id": 0, "type": "table", "value": "member" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "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", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "B-TABLE", "I-TABLE", "O", "O" ]
114
book_review
bird:test.json:594
List the titles of books in ascending alphabetical order.
SELECT Title FROM book ORDER BY Title ASC
[ "List", "the", "titles", "of", "books", "in", "ascending", "alphabetical", "order", "." ]
[ { "id": 1, "type": "column", "value": "title" }, { "id": 0, "type": "table", "value": "book" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "O" ]
115
baseball_1
spider:train_spider.json:3678
What is the total salary expenses of team Boston Red Stockings in 2010?
SELECT sum(T1.salary) FROM salary AS T1 JOIN team AS T2 ON T1.team_id = T2.team_id_br WHERE T2.name = 'Boston Red Stockings' AND T1.year = 2010
[ "What", "is", "the", "total", "salary", "expenses", "of", "team", "Boston", "Red", "Stockings", "in", "2010", "?" ]
[ { "id": 6, "type": "value", "value": "Boston Red Stockings" }, { "id": 4, "type": "column", "value": "team_id_br" }, { "id": 3, "type": "column", "value": "team_id" }, { "id": 0, "type": "table", "value": "salary" }, { "id": 2, "type": "column", "value": "salary" }, { "id": 1, "type": "table", "value": "team" }, { "id": 5, "type": "column", "value": "name" }, { "id": 7, "type": "column", "value": "year" }, { "id": 8, "type": "value", "value": "2010" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 7 ] }, { "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": [ 8, 9, 10 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [ 12 ] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "B-VALUE", "I-VALUE", "I-VALUE", "O", "B-VALUE", "O" ]
116
movies_4
bird:train.json:449
List the names of the production companies that made at least 200 movies.
SELECT T1.company_name FROM production_company AS T1 INNER JOIN movie_company AS T2 ON T1.company_id = T2.company_id GROUP BY T1.company_id HAVING COUNT(T2.movie_id) > 200
[ "List", "the", "names", "of", "the", "production", "companies", "that", "made", "at", "least", "200", "movies", "." ]
[ { "id": 2, "type": "table", "value": "production_company" }, { "id": 3, "type": "table", "value": "movie_company" }, { "id": 1, "type": "column", "value": "company_name" }, { "id": 0, "type": "column", "value": "company_id" }, { "id": 5, "type": "column", "value": "movie_id" }, { "id": 4, "type": "value", "value": "200" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 11 ] }, { "entity_id": 5, "token_idxs": [ 12 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
118
aircraft
spider:train_spider.json:4823
List the name of the aircraft that has been named winning aircraft the most number of times.
SELECT T1.Aircraft FROM aircraft AS T1 JOIN MATCH AS T2 ON T1.Aircraft_ID = T2.Winning_Aircraft GROUP BY T2.Winning_Aircraft ORDER BY COUNT(*) DESC LIMIT 1
[ "List", "the", "name", "of", "the", "aircraft", "that", "has", "been", "named", "winning", "aircraft", "the", "most", "number", "of", "times", "." ]
[ { "id": 0, "type": "column", "value": "winning_aircraft" }, { "id": 4, "type": "column", "value": "aircraft_id" }, { "id": 1, "type": "column", "value": "aircraft" }, { "id": 2, "type": "table", "value": "aircraft" }, { "id": 3, "type": "table", "value": "match" } ]
[ { "entity_id": 0, "token_idxs": [ 10, 11 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "O" ]
119
store_1
spider:train_spider.json:582
In which country does Roberto Almeida?
SELECT country FROM customers WHERE first_name = "Roberto" AND last_name = "Almeida";
[ "In", "which", "country", "does", "Roberto", "Almeida", "?" ]
[ { "id": 2, "type": "column", "value": "first_name" }, { "id": 0, "type": "table", "value": "customers" }, { "id": 4, "type": "column", "value": "last_name" }, { "id": 1, "type": "column", "value": "country" }, { "id": 3, "type": "column", "value": "Roberto" }, { "id": 5, "type": "column", "value": "Almeida" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 4 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 5 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-COLUMN", "B-COLUMN", "O" ]
120
theme_gallery
spider:train_spider.json:1672
What are the names of artists that have not had any exhibitions?
SELECT name FROM artist WHERE artist_id NOT IN (SELECT artist_id FROM exhibition)
[ "What", "are", "the", "names", "of", "artists", "that", "have", "not", "had", "any", "exhibitions", "?" ]
[ { "id": 3, "type": "table", "value": "exhibition" }, { "id": 2, "type": "column", "value": "artist_id" }, { "id": 0, "type": "table", "value": "artist" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "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", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
121
works_cycles
bird:train.json:7304
Among the salable products from the mountain product line, how many of them have the most reviews?
SELECT SUM(CASE WHEN T2.ProductLine = 'M' THEN 1 ELSE 0 END) FROM ProductReview AS T1 INNER JOIN Product AS T2 ON T1.ProductID = T2.ProductID WHERE T2.FinishedGoodsFlag = 1 GROUP BY T1.ProductID ORDER BY COUNT(T1.ProductReviewID) DESC LIMIT 1
[ "Among", "the", "salable", "products", "from", "the", "mountain", "product", "line", ",", "how", "many", "of", "them", "have", "the", "most", "reviews", "?" ]
[ { "id": 3, "type": "column", "value": "finishedgoodsflag" }, { "id": 5, "type": "column", "value": "productreviewid" }, { "id": 1, "type": "table", "value": "productreview" }, { "id": 7, "type": "column", "value": "productline" }, { "id": 0, "type": "column", "value": "productid" }, { "id": 2, "type": "table", "value": "product" }, { "id": 4, "type": "value", "value": "1" }, { "id": 6, "type": "value", "value": "0" }, { "id": 8, "type": "value", "value": "M" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 8 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "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", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
122
thrombosis_prediction
bird:dev.json:1235
What are the patient's diagnosis for those who has lower red blood blood cell? State their ID and age.
SELECT DISTINCT T1.Diagnosis, T1.ID , STRFTIME('%Y', CURRENT_TIMESTAMP) -STRFTIME('%Y', T1.Birthday) FROM Patient AS T1 INNER JOIN Laboratory AS T2 ON T1.ID = T2.ID WHERE T2.RBC < 3.5
[ "What", "are", "the", "patient", "'s", "diagnosis", "for", "those", "who", "has", "lower", "red", "blood", "blood", "cell", "?", "State", "their", "ID", "and", "age", "." ]
[ { "id": 3, "type": "table", "value": "laboratory" }, { "id": 0, "type": "column", "value": "diagnosis" }, { "id": 7, "type": "column", "value": "birthday" }, { "id": 2, "type": "table", "value": "patient" }, { "id": 4, "type": "column", "value": "rbc" }, { "id": 5, "type": "value", "value": "3.5" }, { "id": 1, "type": "column", "value": "id" }, { "id": 6, "type": "value", "value": "%Y" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [ 18 ] }, { "entity_id": 2, "token_idxs": [ 3 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O" ]
123
books
bird:train.json:5952
What is the name of the first book written by J.K Rowling?
SELECT T1.title FROM book AS T1 INNER JOIN book_author AS T2 ON T1.book_id = T2.book_id INNER JOIN author AS T3 ON T3.author_id = T2.author_id WHERE T3.author_name = 'J.K. Rowling' ORDER BY T1.publication_date ASC LIMIT 1
[ "What", "is", "the", "name", "of", "the", "first", "book", "written", "by", "J.K", "Rowling", "?" ]
[ { "id": 4, "type": "column", "value": "publication_date" }, { "id": 3, "type": "value", "value": "J.K. Rowling" }, { "id": 2, "type": "column", "value": "author_name" }, { "id": 6, "type": "table", "value": "book_author" }, { "id": 7, "type": "column", "value": "author_id" }, { "id": 8, "type": "column", "value": "book_id" }, { "id": 1, "type": "table", "value": "author" }, { "id": 0, "type": "column", "value": "title" }, { "id": 5, "type": "table", "value": "book" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 2, 3 ] }, { "entity_id": 3, "token_idxs": [ 10, 11 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 7 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "B-TABLE", "O", "O", "B-VALUE", "I-VALUE", "O" ]
124
movies_4
bird:train.json:535
What percentage of films are made in the US?
SELECT CAST(COUNT(CASE WHEN T3.COUNTry_iso_code = 'US' THEN T1.movie_id ELSE NULL END) AS REAL) * 100 / COUNT(T1.movie_id) FROM movie AS T1 INNER JOIN production_COUNTry AS T2 ON T1.movie_id = T2.movie_id INNER JOIN COUNTry AS T3 ON T2.COUNTry_id = T3.COUNTry_id
[ "What", "percentage", "of", "films", "are", "made", "in", "the", "US", "?" ]
[ { "id": 2, "type": "table", "value": "production_country" }, { "id": 6, "type": "column", "value": "country_iso_code" }, { "id": 3, "type": "column", "value": "country_id" }, { "id": 5, "type": "column", "value": "movie_id" }, { "id": 0, "type": "table", "value": "country" }, { "id": 1, "type": "table", "value": "movie" }, { "id": 4, "type": "value", "value": "100" }, { "id": 7, "type": "value", "value": "US" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 8 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "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" ]
125
aan_1
bird:test.json:1023
What are the names of the top 3 affiliations that have the most papers in year 2009?
SELECT T3.name FROM Paper AS T1 JOIN Author_list AS T2 ON T1.paper_id = T2.paper_id JOIN Affiliation AS T3 ON T2.affiliation_id = T3.affiliation_id WHERE T1.year = 2009 GROUP BY T2.affiliation_id ORDER BY count(*) DESC LIMIT 3
[ "What", "are", "the", "names", "of", "the", "top", "3", "affiliations", "that", "have", "the", "most", "papers", "in", "year", "2009", "?" ]
[ { "id": 0, "type": "column", "value": "affiliation_id" }, { "id": 2, "type": "table", "value": "affiliation" }, { "id": 6, "type": "table", "value": "author_list" }, { "id": 7, "type": "column", "value": "paper_id" }, { "id": 5, "type": "table", "value": "paper" }, { "id": 1, "type": "column", "value": "name" }, { "id": 3, "type": "column", "value": "year" }, { "id": 4, "type": "value", "value": "2009" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [ 15 ] }, { "entity_id": 4, "token_idxs": [ 16 ] }, { "entity_id": 5, "token_idxs": [ 13 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 14 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "B-COLUMN", "B-VALUE", "O" ]
126
financial
bird:dev.json:157
What is the number of committed crimes in 1995 in the district of the account with the id 532?
SELECT T1.A15 FROM district AS T1 INNER JOIN `account` AS T2 ON T1.district_id = T2.district_id WHERE T2.account_id = 532
[ "What", "is", "the", "number", "of", "committed", "crimes", "in", "1995", "in", "the", "district", "of", "the", "account", "with", "the", "i", "d", "532", "?" ]
[ { "id": 5, "type": "column", "value": "district_id" }, { "id": 3, "type": "column", "value": "account_id" }, { "id": 1, "type": "table", "value": "district" }, { "id": 2, "type": "table", "value": "account" }, { "id": 0, "type": "column", "value": "a15" }, { "id": 4, "type": "value", "value": "532" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 11 ] }, { "entity_id": 2, "token_idxs": [ 14 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 19 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-VALUE", "O" ]
127
soccer_2016
bird:train.json:1836
How many players with left-hand batting style are from India?
SELECT SUM(CASE WHEN T1.Batting_hand = 'Left-hand bat' THEN 1 ELSE 0 END) AS cnt FROM Batting_Style AS T1 INNER JOIN Player AS T2 ON T1.Batting_Id = T2.Batting_hand INNER JOIN Country AS T3 ON T2.Country_Name = T3.Country_Id WHERE T3.Country_Name = 'India'
[ "How", "many", "players", "with", "left", "-", "hand", "batting", "style", "are", "from", "India", "?" ]
[ { "id": 3, "type": "table", "value": "batting_style" }, { "id": 10, "type": "value", "value": "Left-hand bat" }, { "id": 1, "type": "column", "value": "country_name" }, { "id": 8, "type": "column", "value": "batting_hand" }, { "id": 5, "type": "column", "value": "country_id" }, { "id": 7, "type": "column", "value": "batting_id" }, { "id": 0, "type": "table", "value": "country" }, { "id": 4, "type": "table", "value": "player" }, { "id": 2, "type": "value", "value": "India" }, { "id": 6, "type": "value", "value": "0" }, { "id": 9, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 11 ] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [ 2 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 7 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [ 4, 5, 6 ] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "I-VALUE", "B-COLUMN", "B-TABLE", "O", "O", "B-VALUE", "O" ]
129
car_road_race
bird:test.json:1343
How many drivers use each constructor?
SELECT CONSTRUCTOR , COUNT(*) FROM driver GROUP BY CONSTRUCTOR
[ "How", "many", "drivers", "use", "each", "constructor", "?" ]
[ { "id": 1, "type": "column", "value": "constructor" }, { "id": 0, "type": "table", "value": "driver" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "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" ]
130
mondial_geo
bird:train.json:8242
Which country has the biggest percentage of the albanian ethnic group?
SELECT T1.Name FROM country AS T1 INNER JOIN ethnicGroup AS T2 ON T1.Code = T2.Country WHERE T2.Name = 'Albanian' ORDER BY T2.Percentage DESC LIMIT 1
[ "Which", "country", "has", "the", "biggest", "percentage", "of", "the", "albanian", "ethnic", "group", "?" ]
[ { "id": 2, "type": "table", "value": "ethnicgroup" }, { "id": 4, "type": "column", "value": "percentage" }, { "id": 3, "type": "value", "value": "Albanian" }, { "id": 1, "type": "table", "value": "country" }, { "id": 6, "type": "column", "value": "country" }, { "id": 0, "type": "column", "value": "name" }, { "id": 5, "type": "column", "value": "code" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 9, 10 ] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [ 5 ] }, { "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", "O", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "B-TABLE", "I-TABLE", "O" ]
131
products_gen_characteristics
spider:train_spider.json:5581
What is the description of the product category with the code 'Spices'?
SELECT product_category_description FROM ref_product_categories WHERE product_category_code = "Spices"
[ "What", "is", "the", "description", "of", "the", "product", "category", "with", "the", "code", "'", "Spices", "'", "?" ]
[ { "id": 1, "type": "column", "value": "product_category_description" }, { "id": 0, "type": "table", "value": "ref_product_categories" }, { "id": 2, "type": "column", "value": "product_category_code" }, { "id": 3, "type": "column", "value": "Spices" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 8 ] }, { "entity_id": 2, "token_idxs": [ 6, 7 ] }, { "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", "I-COLUMN", "B-COLUMN", "O", "O", "O", "B-COLUMN", "O", "O" ]
132
movie_2
bird:test.json:1831
Find the titles of all movies sorted by their ratings.
SELECT title FROM movies ORDER BY rating
[ "Find", "the", "titles", "of", "all", "movies", "sorted", "by", "their", "ratings", "." ]
[ { "id": 0, "type": "table", "value": "movies" }, { "id": 2, "type": "column", "value": "rating" }, { "id": 1, "type": "column", "value": "title" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O" ]
133
soccer_2016
bird:train.json:1890
Give the player id of the player who was at the non-striker end for the most number of balls in the match 501219.
SELECT Ball_Id FROM Ball_by_Ball WHERE Non_Striker = Ball_Id ORDER BY Ball_Id DESC LIMIT 1
[ "Give", "the", "player", "i", "d", "of", "the", "player", "who", "was", "at", "the", "non", "-", "striker", "end", "for", "the", "most", "number", "of", "balls", "in", "the", "match", "501219", "." ]
[ { "id": 0, "type": "table", "value": "ball_by_ball" }, { "id": 2, "type": "column", "value": "non_striker" }, { "id": 1, "type": "column", "value": "ball_id" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 21, 22 ] }, { "entity_id": 2, "token_idxs": [ 12, 13, 14 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O" ]
134
warehouse_1
bird:test.json:1736
For each content, what is the total value and number of boxes?
SELECT sum(value) , count(*) , CONTENTS FROM boxes GROUP BY CONTENTS
[ "For", "each", "content", ",", "what", "is", "the", "total", "value", "and", "number", "of", "boxes", "?" ]
[ { "id": 1, "type": "column", "value": "contents" }, { "id": 0, "type": "table", "value": "boxes" }, { "id": 2, "type": "column", "value": "value" } ]
[ { "entity_id": 0, "token_idxs": [ 12 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "O" ]
135
allergy_1
spider:train_spider.json:504
How many students are affected by cat allergies?
SELECT count(*) FROM Has_allergy WHERE Allergy = "Cat"
[ "How", "many", "students", "are", "affected", "by", "cat", "allergies", "?" ]
[ { "id": 0, "type": "table", "value": "has_allergy" }, { "id": 1, "type": "column", "value": "allergy" }, { "id": 2, "type": "column", "value": "Cat" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 7 ] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "B-COLUMN", "O" ]
136
restaurant
bird:train.json:1688
Identify all restaurants in Contra Costa County by id.
SELECT T1.id_restaurant FROM location AS T1 INNER JOIN geographic AS T2 ON T1.city = T2.city WHERE T2.county = 'contra costa county'
[ "Identify", "all", "restaurants", "in", "Contra", "Costa", "County", "by", "i", "d." ]
[ { "id": 4, "type": "value", "value": "contra costa county" }, { "id": 0, "type": "column", "value": "id_restaurant" }, { "id": 2, "type": "table", "value": "geographic" }, { "id": 1, "type": "table", "value": "location" }, { "id": 3, "type": "column", "value": "county" }, { "id": 5, "type": "column", "value": "city" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 4, 5 ] }, { "entity_id": 5, "token_idxs": [ 6 ] }, { "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-VALUE", "I-VALUE", "B-COLUMN", "O", "O", "O" ]
137
election
spider:train_spider.json:2777
For each party, return the name of the party and the number of delegates from that party.
SELECT T2.Party , COUNT(*) FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID GROUP BY T1.Party
[ "For", "each", "party", ",", "return", "the", "name", "of", "the", "party", "and", "the", "number", "of", "delegates", "from", "that", "party", "." ]
[ { "id": 1, "type": "table", "value": "election" }, { "id": 3, "type": "column", "value": "party_id" }, { "id": 0, "type": "column", "value": "party" }, { "id": 2, "type": "table", "value": "party" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 2 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
138
wedding
spider:train_spider.json:1634
Show all opening years and the number of churches that opened in that year.
SELECT open_date , count(*) FROM church GROUP BY open_date
[ "Show", "all", "opening", "years", "and", "the", "number", "of", "churches", "that", "opened", "in", "that", "year", "." ]
[ { "id": 1, "type": "column", "value": "open_date" }, { "id": 0, "type": "table", "value": "church" } ]
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [ 10 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "O", "O", "O", "O" ]
139
flight_company
spider:train_spider.json:6382
how many airports are there in each country?
SELECT count(*) , country FROM airport GROUP BY country
[ "how", "many", "airports", "are", "there", "in", "each", "country", "?" ]
[ { "id": 0, "type": "table", "value": "airport" }, { "id": 1, "type": "column", "value": "country" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 7 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "O" ]
140
game_1
spider:train_spider.json:5999
How many sports do we have?
SELECT count(DISTINCT sportname) FROM Sportsinfo
[ "How", "many", "sports", "do", "we", "have", "?" ]
[ { "id": 0, "type": "table", "value": "sportsinfo" }, { "id": 1, "type": "column", "value": "sportname" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "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" ]
141
beer_factory
bird:train.json:5297
Among the customers not subscribed to the mailing list, what percentage has given three or more stars in a review?
SELECT CAST(COUNT(CASE WHEN T2.StarRating > 3 THEN 1 ELSE NULL END) AS REAL) * 100 / COUNT(T2.CustomerID) FROM customers AS T1 INNER JOIN rootbeerreview AS T2 ON T1.CustomerID = T2.CustomerID WHERE T1.SubscribedToEmailList = 'FALSE'
[ "Among", "the", "customers", "not", "subscribed", "to", "the", "mailing", "list", ",", "what", "percentage", "has", "given", "three", "or", "more", "stars", "in", "a", "review", "?" ]
[ { "id": 2, "type": "column", "value": "subscribedtoemaillist" }, { "id": 1, "type": "table", "value": "rootbeerreview" }, { "id": 4, "type": "column", "value": "customerid" }, { "id": 7, "type": "column", "value": "starrating" }, { "id": 0, "type": "table", "value": "customers" }, { "id": 3, "type": "value", "value": "FALSE" }, { "id": 5, "type": "value", "value": "100" }, { "id": 6, "type": "value", "value": "1" }, { "id": 8, "type": "value", "value": "3" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 20 ] }, { "entity_id": 2, "token_idxs": [ 4, 5, 6, 7, 8 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 17, 18 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-TABLE", "O" ]
142
hockey
bird:train.json:7782
What is the average winning rate of the Montreal Canadiens in the Stanley Cup finals?
SELECT SUM(T2.W / T2.G) / SUM(T2.G + T2.W) FROM Teams AS T1 INNER JOIN TeamsSC AS T2 ON T1.tmID = T2.tmID AND T1.year = T2.year WHERE T1.name = 'Montreal Canadiens'
[ "What", "is", "the", "average", "winning", "rate", "of", "the", "Montreal", "Canadiens", "in", "the", "Stanley", "Cup", "finals", "?" ]
[ { "id": 3, "type": "value", "value": "Montreal Canadiens" }, { "id": 1, "type": "table", "value": "teamssc" }, { "id": 0, "type": "table", "value": "teams" }, { "id": 2, "type": "column", "value": "name" }, { "id": 4, "type": "column", "value": "tmid" }, { "id": 5, "type": "column", "value": "year" }, { "id": 6, "type": "column", "value": "w" }, { "id": 7, "type": "column", "value": "g" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "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", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "O", "O", "O", "O", "O", "O" ]
143
icfp_1
spider:train_spider.json:2864
What are the titles of papers published by "Jeremy Gibbons"?
SELECT t3.title FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid WHERE t1.fname = "Jeremy" AND t1.lname = "Gibbons"
[ "What", "are", "the", "titles", "of", "papers", "published", "by", "\"", "Jeremy", "Gibbons", "\"", "?" ]
[ { "id": 3, "type": "table", "value": "authorship" }, { "id": 2, "type": "table", "value": "authors" }, { "id": 4, "type": "column", "value": "paperid" }, { "id": 8, "type": "column", "value": "Gibbons" }, { "id": 1, "type": "table", "value": "papers" }, { "id": 6, "type": "column", "value": "Jeremy" }, { "id": 9, "type": "column", "value": "authid" }, { "id": 0, "type": "column", "value": "title" }, { "id": 5, "type": "column", "value": "fname" }, { "id": 7, "type": "column", "value": "lname" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 9 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [ 10 ] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "B-COLUMN", "O", "O" ]
144
movies_4
bird:train.json:454
How many horror movies are there?
SELECT COUNT(T1.movie_id) FROM movie_genres AS T1 INNER JOIN genre AS T2 ON T1.genre_id = T2.genre_id WHERE T2.genre_name = 'Horror'
[ "How", "many", "horror", "movies", "are", "there", "?" ]
[ { "id": 0, "type": "table", "value": "movie_genres" }, { "id": 2, "type": "column", "value": "genre_name" }, { "id": 4, "type": "column", "value": "movie_id" }, { "id": 5, "type": "column", "value": "genre_id" }, { "id": 3, "type": "value", "value": "Horror" }, { "id": 1, "type": "table", "value": "genre" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 2 ] }, { "entity_id": 4, "token_idxs": [ 3 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-VALUE", "B-COLUMN", "O", "B-TABLE", "O" ]
145
architecture
spider:train_spider.json:6960
How many architects haven't built a mill before year 1850?
SELECT count(*) FROM architect WHERE id NOT IN ( SELECT architect_id FROM mill WHERE built_year < 1850 );
[ "How", "many", "architects", "have", "n't", "built", "a", "mill", "before", "year", "1850", "?" ]
[ { "id": 3, "type": "column", "value": "architect_id" }, { "id": 4, "type": "column", "value": "built_year" }, { "id": 0, "type": "table", "value": "architect" }, { "id": 2, "type": "table", "value": "mill" }, { "id": 5, "type": "value", "value": "1850" }, { "id": 1, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 5, 6 ] }, { "entity_id": 5, "token_idxs": [ 10 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "I-COLUMN", "B-TABLE", "O", "O", "B-VALUE", "O" ]
146
government_shift
bird:test.json:355
List details of all the channel in alphabetical order .
select channel_details from channels order by channel_details
[ "List", "details", "of", "all", "the", "channel", "in", "alphabetical", "order", "." ]
[ { "id": 1, "type": "column", "value": "channel_details" }, { "id": 0, "type": "table", "value": "channels" } ]
[ { "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" ]
147
program_share
spider:train_spider.json:3766
Find the name of the program that is broadcast most frequently.
SELECT t1.name FROM program AS t1 JOIN broadcast AS t2 ON t1.program_id = t2.program_id GROUP BY t2.program_id ORDER BY count(*) DESC LIMIT 1
[ "Find", "the", "name", "of", "the", "program", "that", "is", "broadcast", "most", "frequently", "." ]
[ { "id": 0, "type": "column", "value": "program_id" }, { "id": 3, "type": "table", "value": "broadcast" }, { "id": 2, "type": "table", "value": "program" }, { "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": [ 8 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-TABLE", "O", "O", "O" ]
148
public_review_platform
bird:train.json:3852
Among the Yelp_Businesses in Arizona, how many of them do not provide alcohol?
SELECT COUNT(T2.business_id) FROM Attributes AS T1 INNER JOIN Business_Attributes AS T2 ON T1.attribute_id = T2.attribute_id INNER JOIN Business AS T3 ON T2.business_id = T3.business_id WHERE T1.attribute_name LIKE 'Alcohol' AND T2.attribute_value LIKE 'none' AND T3.state LIKE 'AZ'
[ "Among", "the", "Yelp_Businesses", "in", "Arizona", ",", "how", "many", "of", "them", "do", "not", "provide", "alcohol", "?" ]
[ { "id": 3, "type": "table", "value": "business_attributes" }, { "id": 6, "type": "column", "value": "attribute_value" }, { "id": 4, "type": "column", "value": "attribute_name" }, { "id": 10, "type": "column", "value": "attribute_id" }, { "id": 1, "type": "column", "value": "business_id" }, { "id": 2, "type": "table", "value": "attributes" }, { "id": 0, "type": "table", "value": "business" }, { "id": 5, "type": "value", "value": "Alcohol" }, { "id": 8, "type": "column", "value": "state" }, { "id": 7, "type": "value", "value": "none" }, { "id": 9, "type": "value", "value": "AZ" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "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-TABLE", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "O" ]
149
book_publishing_company
bird:train.json:182
Which employee has the lowest job level. State the first name, last name and when he /she was hired.
SELECT fname, lname, hire_date FROM employee ORDER BY job_lvl LIMIT 1
[ "Which", "employee", "has", "the", "lowest", "job", "level", ".", "State", "the", "first", "name", ",", "last", "name", "and", "when", "he", "/she", "was", "hired", "." ]
[ { "id": 3, "type": "column", "value": "hire_date" }, { "id": 0, "type": "table", "value": "employee" }, { "id": 4, "type": "column", "value": "job_lvl" }, { "id": 1, "type": "column", "value": "fname" }, { "id": 2, "type": "column", "value": "lname" } ]
[ { "entity_id": 0, "token_idxs": [ 1 ] }, { "entity_id": 1, "token_idxs": [ 14 ] }, { "entity_id": 2, "token_idxs": [ 11 ] }, { "entity_id": 3, "token_idxs": [ 20 ] }, { "entity_id": 4, "token_idxs": [ 5, 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", "B-TABLE", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
150
student_loan
bird:train.json:4564
List the names of the disabled students who were absent from school for more than 5 months.
SELECT T1.name FROM longest_absense_from_school AS T1 INNER JOIN disabled AS T2 ON T1.name = T2.name WHERE T1.month > 5
[ "List", "the", "names", "of", "the", "disabled", "students", "who", "were", "absent", "from", "school", "for", "more", "than", "5", "months", "." ]
[ { "id": 1, "type": "table", "value": "longest_absense_from_school" }, { "id": 2, "type": "table", "value": "disabled" }, { "id": 3, "type": "column", "value": "month" }, { "id": 0, "type": "column", "value": "name" }, { "id": 4, "type": "value", "value": "5" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 9, 10, 11 ] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [ 16 ] }, { "entity_id": 4, "token_idxs": [ 15 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "B-TABLE", "I-TABLE", "I-TABLE", "O", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
151
student_loan
bird:train.json:4519
State the number of male students who do not have payment due.
SELECT COUNT(T1.name) FROM no_payment_due AS T1 INNER JOIN male AS T2 ON T2.name = T1.name WHERE T1.bool = 'pos'
[ "State", "the", "number", "of", "male", "students", "who", "do", "not", "have", "payment", "due", "." ]
[ { "id": 0, "type": "table", "value": "no_payment_due" }, { "id": 1, "type": "table", "value": "male" }, { "id": 2, "type": "column", "value": "bool" }, { "id": 4, "type": "column", "value": "name" }, { "id": 3, "type": "value", "value": "pos" } ]
[ { "entity_id": 0, "token_idxs": [ 10, 11 ] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 2 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-TABLE", "I-TABLE", "O" ]
153
thrombosis_prediction
bird:dev.json:1251
How many patients with an Ig G higher than normal?
SELECT COUNT(DISTINCT T1.ID) FROM Patient AS T1 INNER JOIN Laboratory AS T2 ON T1.ID = T2.ID INNER JOIN Examination AS T3 ON T3.ID = T2.ID WHERE T2.IGG >= 2000
[ "How", "many", "patients", "with", "an", "Ig", "G", "higher", "than", "normal", "?" ]
[ { "id": 0, "type": "table", "value": "examination" }, { "id": 5, "type": "table", "value": "laboratory" }, { "id": 4, "type": "table", "value": "patient" }, { "id": 2, "type": "value", "value": "2000" }, { "id": 1, "type": "column", "value": "igg" }, { "id": 3, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 5, 6 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 2 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O" ]
154
bakery_1
bird:test.json:1588
What are the ids of customers who spend more than 5 on average for each good?
SELECT T3.CustomerId FROM goods AS T1 JOIN items AS T2 ON T1.id = T2.item JOIN receipts AS T3 ON T2.receipt = T3.ReceiptNumber GROUP BY T3.CustomerId HAVING avg(T1.price) > 5
[ "What", "are", "the", "ids", "of", "customers", "who", "spend", "more", "than", "5", "on", "average", "for", "each", "good", "?" ]
[ { "id": 6, "type": "column", "value": "receiptnumber" }, { "id": 0, "type": "column", "value": "customerid" }, { "id": 1, "type": "table", "value": "receipts" }, { "id": 5, "type": "column", "value": "receipt" }, { "id": 3, "type": "table", "value": "goods" }, { "id": 4, "type": "table", "value": "items" }, { "id": 7, "type": "column", "value": "price" }, { "id": 9, "type": "column", "value": "item" }, { "id": 8, "type": "column", "value": "id" }, { "id": 2, "type": "value", "value": "5" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 10 ] }, { "entity_id": 3, "token_idxs": [ 15 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [ 3 ] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "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", "O", "O", "B-VALUE", "O", "O", "O", "O", "B-TABLE", "O" ]
155
movie_platform
bird:train.json:99
Please list the names of the movies that user 94978 scored as 5.
SELECT T2.movie_title FROM ratings AS T1 INNER JOIN movies AS T2 ON T1.movie_id = T2.movie_id WHERE T1.rating_score = 5 AND T1.user_id = 94978
[ "Please", "list", "the", "names", "of", "the", "movies", "that", "user", "94978", "scored", "as", "5", "." ]
[ { "id": 4, "type": "column", "value": "rating_score" }, { "id": 0, "type": "column", "value": "movie_title" }, { "id": 3, "type": "column", "value": "movie_id" }, { "id": 1, "type": "table", "value": "ratings" }, { "id": 6, "type": "column", "value": "user_id" }, { "id": 2, "type": "table", "value": "movies" }, { "id": 7, "type": "value", "value": "94978" }, { "id": 5, "type": "value", "value": "5" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "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": [ 12 ] }, { "entity_id": 6, "token_idxs": [ 8 ] }, { "entity_id": 7, "token_idxs": [ 9 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "B-COLUMN", "B-VALUE", "O", "O", "B-VALUE", "O" ]
156
works_cycles
bird:train.json:7324
Among the employees in Adventure Works, calculate the percentage of them working as sales representatives.
SELECT CAST(SUM(CASE WHEN JobTitle = 'Sales Representative' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(BusinessEntityID) FROM Employee
[ "Among", "the", "employees", "in", "Adventure", "Works", ",", "calculate", "the", "percentage", "of", "them", "working", "as", "sales", "representatives", "." ]
[ { "id": 6, "type": "value", "value": "Sales Representative" }, { "id": 2, "type": "column", "value": "businessentityid" }, { "id": 0, "type": "table", "value": "employee" }, { "id": 5, "type": "column", "value": "jobtitle" }, { "id": 1, "type": "value", "value": "100" }, { "id": 3, "type": "value", "value": "0" }, { "id": 4, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 14, 15 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "O" ]
157
world
bird:train.json:7895
How many countries have no GNP?
SELECT COUNT(*) FROM Country WHERE GNP = 0
[ "How", "many", "countries", "have", "no", "GNP", "?" ]
[ { "id": 0, "type": "table", "value": "country" }, { "id": 1, "type": "column", "value": "gnp" }, { "id": 2, "type": "value", "value": "0" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "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" ]
159
airline
bird:train.json:5849
Tell the number of flights that landed at Lake Charles Regional Airport on 2018/8/15.
SELECT COUNT(T1.Code) FROM Airports AS T1 INNER JOIN Airlines AS T2 ON T1.Code = T2.DEST WHERE T2.FL_DATE = '2018/8/15' AND T1.Description = 'Lake Charles, LA: Lake Charles Regional'
[ "Tell", "the", "number", "of", "flights", "that", "landed", "at", "Lake", "Charles", "Regional", "Airport", "on", "2018/8/15", "." ]
[ { "id": 7, "type": "value", "value": "Lake Charles, LA: Lake Charles Regional" }, { "id": 6, "type": "column", "value": "description" }, { "id": 5, "type": "value", "value": "2018/8/15" }, { "id": 0, "type": "table", "value": "airports" }, { "id": 1, "type": "table", "value": "airlines" }, { "id": 4, "type": "column", "value": "fl_date" }, { "id": 2, "type": "column", "value": "code" }, { "id": 3, "type": "column", "value": "dest" } ]
[ { "entity_id": 0, "token_idxs": [ 11 ] }, { "entity_id": 1, "token_idxs": [ 9 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 13 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 6, 7, 8, 10 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "B-TABLE", "B-VALUE", "B-TABLE", "O", "B-VALUE", "O" ]
160
world
bird:train.json:7840
Among the countries that officially use the English language, what country has the highest capital?
SELECT T1.Code FROM Country AS T1 INNER JOIN CountryLanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = 'English' AND T2.IsOfficial = 'T' ORDER BY T1.Capital DESC LIMIT 1
[ "Among", "the", "countries", "that", "officially", "use", "the", "English", "language", ",", "what", "country", "has", "the", "highest", "capital", "?" ]
[ { "id": 2, "type": "table", "value": "countrylanguage" }, { "id": 4, "type": "column", "value": "countrycode" }, { "id": 7, "type": "column", "value": "isofficial" }, { "id": 5, "type": "column", "value": "language" }, { "id": 1, "type": "table", "value": "country" }, { "id": 3, "type": "column", "value": "capital" }, { "id": 6, "type": "value", "value": "English" }, { "id": 0, "type": "column", "value": "code" }, { "id": 8, "type": "value", "value": "T" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 11 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 15 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 8 ] }, { "entity_id": 6, "token_idxs": [ 7 ] }, { "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", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O" ]
161
music_platform_2
bird:train.json:7985
How many ratings of 5 have been given to the podcast "Please Excuse My Dead Aunt Sally"?
SELECT COUNT(T2.rating) FROM podcasts AS T1 INNER JOIN reviews AS T2 ON T2.podcast_id = T1.podcast_id WHERE T1.title = 'Please Excuse My Dead Aunt Sally' AND T2.rating = 5
[ "How", "many", "ratings", "of", "5", "have", "been", "given", "to", "the", "podcast", "\"", "Please", "Excuse", "My", "Dead", "Aunt", "Sally", "\"", "?" ]
[ { "id": 5, "type": "value", "value": "Please Excuse My Dead Aunt Sally" }, { "id": 3, "type": "column", "value": "podcast_id" }, { "id": 0, "type": "table", "value": "podcasts" }, { "id": 1, "type": "table", "value": "reviews" }, { "id": 2, "type": "column", "value": "rating" }, { "id": 4, "type": "column", "value": "title" }, { "id": 6, "type": "value", "value": "5" } ]
[ { "entity_id": 0, "token_idxs": [ 10 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 2 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 12, 13, 14, 15, 16, 17 ] }, { "entity_id": 6, "token_idxs": [ 4 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "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-VALUE", "O", "O", "O", "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O" ]
162
restaurant
bird:train.json:1707
How many American food restaurants are unpopular in Carmel?
SELECT COUNT(id_restaurant) FROM generalinfo WHERE food_type = 'american' AND city = 'carmel' AND review = ( SELECT MIN(review) FROM generalinfo WHERE food_type = 'american' AND city = 'carmel' )
[ "How", "many", "American", "food", "restaurants", "are", "unpopular", "in", "Carmel", "?" ]
[ { "id": 1, "type": "column", "value": "id_restaurant" }, { "id": 0, "type": "table", "value": "generalinfo" }, { "id": 2, "type": "column", "value": "food_type" }, { "id": 3, "type": "value", "value": "american" }, { "id": 5, "type": "value", "value": "carmel" }, { "id": 6, "type": "column", "value": "review" }, { "id": 4, "type": "column", "value": "city" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [ 3 ] }, { "entity_id": 3, "token_idxs": [ 2 ] }, { "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", "O", "B-VALUE", "B-COLUMN", "B-COLUMN", "O", "O", "O", "B-VALUE", "O" ]
163
retail_complains
bird:train.json:254
Which division is Diesel Galloway in?
SELECT T2.division FROM client AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id WHERE T1.first = 'Diesel' AND T1.last = 'Galloway'
[ "Which", "division", "is", "Diesel", "Galloway", "in", "?" ]
[ { "id": 3, "type": "column", "value": "district_id" }, { "id": 0, "type": "column", "value": "division" }, { "id": 2, "type": "table", "value": "district" }, { "id": 7, "type": "value", "value": "Galloway" }, { "id": 1, "type": "table", "value": "client" }, { "id": 5, "type": "value", "value": "Diesel" }, { "id": 4, "type": "column", "value": "first" }, { "id": 6, "type": "column", "value": "last" } ]
[ { "entity_id": 0, "token_idxs": [ 1 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 3 ] }, { "entity_id": 6, "token_idxs": [] }, { "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", "B-COLUMN", "O", "B-VALUE", "B-VALUE", "O", "O" ]
164
wedding
spider:train_spider.json:1648
How many churches have a wedding in year 2016?
SELECT COUNT (DISTINCT church_id) FROM wedding WHERE YEAR = 2016
[ "How", "many", "churches", "have", "a", "wedding", "in", "year", "2016", "?" ]
[ { "id": 3, "type": "column", "value": "church_id" }, { "id": 0, "type": "table", "value": "wedding" }, { "id": 1, "type": "column", "value": "year" }, { "id": 2, "type": "value", "value": "2016" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [ 7 ] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [ 2 ] }, { "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", "B-COLUMN", "B-VALUE", "O" ]
165
card_games
bird:dev.json:495
What was the release date for the set which card "Evacuation" in it?
SELECT T2.releaseDate FROM cards AS T1 INNER JOIN sets AS T2 ON T2.code = T1.setCode WHERE T1.name = 'Evacuation'
[ "What", "was", "the", "release", "date", "for", "the", "set", "which", "card", "\"", "Evacuation", "\"", "in", "it", "?" ]
[ { "id": 0, "type": "column", "value": "releasedate" }, { "id": 4, "type": "value", "value": "Evacuation" }, { "id": 6, "type": "column", "value": "setcode" }, { "id": 1, "type": "table", "value": "cards" }, { "id": 2, "type": "table", "value": "sets" }, { "id": 3, "type": "column", "value": "name" }, { "id": 5, "type": "column", "value": "code" } ]
[ { "entity_id": 0, "token_idxs": [ 3, 4 ] }, { "entity_id": 1, "token_idxs": [ 9 ] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [] }, { "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", "I-COLUMN", "O", "O", "B-TABLE", "O", "B-TABLE", "O", "B-VALUE", "O", "O", "O", "O" ]
166
law_episode
bird:train.json:1302
What is the name of the actors born in the USA?
SELECT name FROM Person WHERE birth_country = 'USA'
[ "What", "is", "the", "name", "of", "the", "actors", "born", "in", "the", "USA", "?" ]
[ { "id": 2, "type": "column", "value": "birth_country" }, { "id": 0, "type": "table", "value": "person" }, { "id": 1, "type": "column", "value": "name" }, { "id": 3, "type": "value", "value": "USA" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 10 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-VALUE", "O" ]
167
csu_1
spider:train_spider.json:2355
What is the average fee for a CSU campus in the year of 2005?
SELECT avg(campusfee) FROM csu_fees WHERE YEAR = 2005
[ "What", "is", "the", "average", "fee", "for", "a", "CSU", "campus", "in", "the", "year", "of", "2005", "?" ]
[ { "id": 3, "type": "column", "value": "campusfee" }, { "id": 0, "type": "table", "value": "csu_fees" }, { "id": 1, "type": "column", "value": "year" }, { "id": 2, "type": "value", "value": "2005" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 11 ] }, { "entity_id": 2, "token_idxs": [ 13 ] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "B-VALUE", "O" ]
168
codebase_community
bird:dev.json:691
Identify the number of adult users who have cast over 5000 upvotes.
SELECT COUNT(Id) FROM users WHERE Age BETWEEN 19 AND 65 AND UpVotes > 5000
[ "Identify", "the", "number", "of", "adult", "users", "who", "have", "cast", "over", "5000", "upvotes", "." ]
[ { "id": 5, "type": "column", "value": "upvotes" }, { "id": 0, "type": "table", "value": "users" }, { "id": 6, "type": "value", "value": "5000" }, { "id": 2, "type": "column", "value": "age" }, { "id": 1, "type": "column", "value": "id" }, { "id": 3, "type": "value", "value": "19" }, { "id": 4, "type": "value", "value": "65" } ]
[ { "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": [ 11 ] }, { "entity_id": 6, "token_idxs": [ 10 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
169
student_loan
bird:train.json:4387
Which school is student829 enrolled in?
SELECT school FROM enrolled WHERE name = 'student829'
[ "Which", "school", "is", "student829", "enrolled", "in", "?" ]
[ { "id": 3, "type": "value", "value": "student829" }, { "id": 0, "type": "table", "value": "enrolled" }, { "id": 1, "type": "column", "value": "school" }, { "id": 2, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 1 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 3 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-COLUMN", "O", "B-VALUE", "B-TABLE", "O", "O" ]
170
formula_1
bird:dev.json:924
Please list the exact dates on which a Formula_1 race took place on the Barcelona-Catalunya circuit.
SELECT T2.date FROM circuits AS T1 INNER JOIN races AS T2 ON T2.circuitID = T1.circuitId WHERE T1.name = 'Circuit de Barcelona-Catalunya'
[ "Please", "list", "the", "exact", "dates", "on", "which", "a", "Formula_1", "race", "took", "place", "on", "the", "Barcelona", "-", "Catalunya", "circuit", "." ]
[ { "id": 4, "type": "value", "value": "Circuit de Barcelona-Catalunya" }, { "id": 5, "type": "column", "value": "circuitid" }, { "id": 1, "type": "table", "value": "circuits" }, { "id": 2, "type": "table", "value": "races" }, { "id": 0, "type": "column", "value": "date" }, { "id": 3, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 17 ] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 13, 14, 15, 16 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "B-TABLE", "O" ]
171
public_review_platform
bird:train.json:3930
Find the location of businesses that has business hours from 9 am to 9 pm every Saturday.
SELECT T1.city FROM Business AS T1 INNER JOIN Business_Hours AS T2 ON T1.business_id = T2.business_id INNER JOIN Days AS T3 ON T2.day_id = T3.day_id WHERE T2.closing_time LIKE '9PM' AND T2.opening_time LIKE '9AM' AND T3.day_of_week LIKE 'Saturday' GROUP BY T1.city
[ "Find", "the", "location", "of", "businesses", "that", "has", "business", "hours", "from", "9", "am", "to", "9", "pm", "every", "Saturday", "." ]
[ { "id": 3, "type": "table", "value": "business_hours" }, { "id": 5, "type": "column", "value": "closing_time" }, { "id": 7, "type": "column", "value": "opening_time" }, { "id": 9, "type": "column", "value": "day_of_week" }, { "id": 11, "type": "column", "value": "business_id" }, { "id": 2, "type": "table", "value": "business" }, { "id": 10, "type": "value", "value": "Saturday" }, { "id": 4, "type": "column", "value": "day_id" }, { "id": 0, "type": "column", "value": "city" }, { "id": 1, "type": "table", "value": "days" }, { "id": 6, "type": "value", "value": "9PM" }, { "id": 8, "type": "value", "value": "9AM" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 13, 14 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [ 10, 11 ] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [ 16 ] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "B-TABLE", "O", "B-VALUE", "I-VALUE", "O", "B-VALUE", "I-VALUE", "O", "B-VALUE", "O" ]
173
cs_semester
bird:train.json:933
In students with a grade of B, how many of them have an intellegence level of 3?
SELECT COUNT(T1.student_id) FROM registration AS T1 INNER JOIN student AS T2 ON T1.student_id = T2.student_id WHERE T1.grade = 'B' AND T2.intelligence = 3
[ "In", "students", "with", "a", "grade", "of", "B", ",", "how", "many", "of", "them", "have", "an", "intellegence", "level", "of", "3", "?" ]
[ { "id": 0, "type": "table", "value": "registration" }, { "id": 5, "type": "column", "value": "intelligence" }, { "id": 2, "type": "column", "value": "student_id" }, { "id": 1, "type": "table", "value": "student" }, { "id": 3, "type": "column", "value": "grade" }, { "id": 4, "type": "value", "value": "B" }, { "id": 6, "type": "value", "value": "3" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 1 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 4 ] }, { "entity_id": 4, "token_idxs": [ 6 ] }, { "entity_id": 5, "token_idxs": [ 14 ] }, { "entity_id": 6, "token_idxs": [ 17 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 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", "B-COLUMN", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "O" ]
174
airline
bird:train.json:5859
How many flights depart to Hartsfield-Jackson Atlanta International from Chicago O'Hare International?
SELECT COUNT(FL_DATE) FROM Airlines WHERE ORIGIN = ( SELECT T2.ORIGIN FROM Airports AS T1 INNER JOIN Airlines AS T2 ON T1.Code = T2.ORIGIN WHERE T1.Description = 'Chicago, IL: Chicago O''Hare International' ) AND DEST = ( SELECT T4.DEST FROM Airports AS T3 INNER JOIN Airlines AS T4 ON T3.Code = T4.DEST WHERE T3.Description = 'Atlanta, GA: Hartsfield-Jackson Atlanta International' )
[ "How", "many", "flights", "depart", "to", "Hartsfield", "-", "Jackson", "Atlanta", "International", "from", "Chicago", "O'Hare", "International", "?" ]
[ { "id": 7, "type": "value", "value": "Atlanta, GA: Hartsfield-Jackson Atlanta International" }, { "id": 6, "type": "value", "value": "Chicago, IL: Chicago O'Hare International" }, { "id": 5, "type": "column", "value": "description" }, { "id": 0, "type": "table", "value": "airlines" }, { "id": 4, "type": "table", "value": "airports" }, { "id": 1, "type": "column", "value": "fl_date" }, { "id": 2, "type": "column", "value": "origin" }, { "id": 3, "type": "column", "value": "dest" }, { "id": 8, "type": "column", "value": "code" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 3 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 10, 11, 12, 13 ] }, { "entity_id": 7, "token_idxs": [ 4, 5, 6, 7, 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-COLUMN", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O" ]
175
car_road_race
bird:test.json:1344
List the most common type of engine used by drivers.
SELECT Engine FROM driver GROUP BY Engine ORDER BY COUNT(*) DESC LIMIT 1
[ "List", "the", "most", "common", "type", "of", "engine", "used", "by", "drivers", "." ]
[ { "id": 0, "type": "table", "value": "driver" }, { "id": 1, "type": "column", "value": "engine" } ]
[ { "entity_id": 0, "token_idxs": [ 9 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O" ]
176
retail_world
bird:train.json:6407
What territories is the Inside Sales Coordinator in charge of?
SELECT T3.TerritoryDescription FROM Employees AS T1 INNER JOIN EmployeeTerritories AS T2 ON T1.EmployeeID = T2.EmployeeID INNER JOIN Territories AS T3 ON T2.TerritoryID = T3.TerritoryID WHERE T1.Title = 'Inside Sales Coordinator'
[ "What", "territories", "is", "the", "Inside", "Sales", "Coordinator", "in", "charge", "of", "?" ]
[ { "id": 3, "type": "value", "value": "Inside Sales Coordinator" }, { "id": 0, "type": "column", "value": "territorydescription" }, { "id": 5, "type": "table", "value": "employeeterritories" }, { "id": 1, "type": "table", "value": "territories" }, { "id": 6, "type": "column", "value": "territoryid" }, { "id": 7, "type": "column", "value": "employeeid" }, { "id": 4, "type": "table", "value": "employees" }, { "id": 2, "type": "column", "value": "title" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 4, 5, 6 ] }, { "entity_id": 4, "token_idxs": [] }, { "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-COLUMN", "O", "B-VALUE", "I-VALUE", "I-VALUE", "O", "O", "O", "O" ]
177
soccer_2016
bird:train.json:2009
How many players are Indians?
SELECT COUNT(T1.Player_Id) FROM Player AS T1 INNER JOIN Country AS T2 ON T1.Country_Name = T2.Country_ID WHERE T2.Country_Name = 'India'
[ "How", "many", "players", "are", "Indians", "?" ]
[ { "id": 2, "type": "column", "value": "country_name" }, { "id": 5, "type": "column", "value": "country_id" }, { "id": 4, "type": "column", "value": "player_id" }, { "id": 1, "type": "table", "value": "country" }, { "id": 0, "type": "table", "value": "player" }, { "id": 3, "type": "value", "value": "India" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 4 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "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" ]
178
cre_Doc_Tracking_DB
spider:train_spider.json:4232
Show the location name and code with the least documents.
SELECT T2.location_name , T1.location_code FROM Document_locations AS T1 JOIN Ref_locations AS T2 ON T1.location_code = T2.location_code GROUP BY T1.location_code ORDER BY count(*) ASC LIMIT 1
[ "Show", "the", "location", "name", "and", "code", "with", "the", "least", "documents", "." ]
[ { "id": 2, "type": "table", "value": "document_locations" }, { "id": 0, "type": "column", "value": "location_code" }, { "id": 1, "type": "column", "value": "location_name" }, { "id": 3, "type": "table", "value": "ref_locations" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "entity_id": 3, "token_idxs": [ 2 ] }, { "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", "B-TABLE", "O" ]
179
movie_3
bird:train.json:9389
List at least 10 films that the customers can rent for more than 5 days.
SELECT T.title FROM ( SELECT T1.title, COUNT(T3.customer_id) AS num FROM film AS T1 INNER JOIN inventory AS T2 ON T1.film_id = T2.film_id INNER JOIN rental AS T3 ON T2.inventory_id = T3.inventory_id WHERE T1.rental_duration > 5 GROUP BY T1.title ) AS T WHERE T.num > 10
[ "List", "at", "least", "10", "films", "that", "the", "customers", "can", "rent", "for", "more", "than", "5", "days", "." ]
[ { "id": 4, "type": "column", "value": "rental_duration" }, { "id": 9, "type": "column", "value": "inventory_id" }, { "id": 6, "type": "column", "value": "customer_id" }, { "id": 8, "type": "table", "value": "inventory" }, { "id": 10, "type": "column", "value": "film_id" }, { "id": 3, "type": "table", "value": "rental" }, { "id": 0, "type": "column", "value": "title" }, { "id": 7, "type": "table", "value": "film" }, { "id": 1, "type": "column", "value": "num" }, { "id": 2, "type": "value", "value": "10" }, { "id": 5, "type": "value", "value": "5" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 3 ] }, { "entity_id": 3, "token_idxs": [ 9 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 13 ] }, { "entity_id": 6, "token_idxs": [ 7 ] }, { "entity_id": 7, "token_idxs": [ 4 ] }, { "entity_id": 8, "token_idxs": [ 10 ] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-VALUE", "B-TABLE", "O", "O", "B-COLUMN", "O", "B-TABLE", "B-TABLE", "O", "O", "B-VALUE", "O", "O" ]
180
professional_basketball
bird:train.json:2874
Among the Most improved Players awarded from 1985-1990, how many player whose country is USA?
SELECT COUNT(DISTINCT T2.playerID) FROM awards_players AS T1 INNER JOIN players AS T2 ON T1.playerID = T2.playerID WHERE T1.award = 'Most Improved Player' AND T2.birthCountry = 'USA' AND T1.year BETWEEN 1985 AND 1990
[ "Among", "the", "Most", "improved", "Players", "awarded", "from", "1985", "-", "1990", ",", "how", "many", "player", "whose", "country", "is", "USA", "?" ]
[ { "id": 4, "type": "value", "value": "Most Improved Player" }, { "id": 0, "type": "table", "value": "awards_players" }, { "id": 5, "type": "column", "value": "birthcountry" }, { "id": 2, "type": "column", "value": "playerid" }, { "id": 1, "type": "table", "value": "players" }, { "id": 3, "type": "column", "value": "award" }, { "id": 7, "type": "column", "value": "year" }, { "id": 8, "type": "value", "value": "1985" }, { "id": 9, "type": "value", "value": "1990" }, { "id": 6, "type": "value", "value": "USA" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 5 ] }, { "entity_id": 4, "token_idxs": [ 2, 3 ] }, { "entity_id": 5, "token_idxs": [ 15 ] }, { "entity_id": 6, "token_idxs": [ 17 ] }, { "entity_id": 7, "token_idxs": [ 13 ] }, { "entity_id": 8, "token_idxs": [ 7 ] }, { "entity_id": 9, "token_idxs": [ 9 ] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-VALUE", "I-VALUE", "B-TABLE", "B-COLUMN", "O", "B-VALUE", "O", "B-VALUE", "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "B-VALUE", "O" ]
181
aircraft
spider:train_spider.json:4798
What is the number of aircraft?
SELECT count(*) FROM aircraft
[ "What", "is", "the", "number", "of", "aircraft", "?" ]
[ { "id": 0, "type": "table", "value": "aircraft" } ]
[ { "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": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "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" ]
182
computer_student
bird:train.json:1037
Which courses were taught by a professor who is not a faculty member?
SELECT DISTINCT T2.course_id FROM person AS T1 INNER JOIN taughtBy AS T2 ON T1.p_id = T2.p_id WHERE T1.professor = 1 AND T1.hasPosition = 0
[ "Which", "courses", "were", "taught", "by", "a", "professor", "who", "is", "not", "a", "faculty", "member", "?" ]
[ { "id": 6, "type": "column", "value": "hasposition" }, { "id": 0, "type": "column", "value": "course_id" }, { "id": 4, "type": "column", "value": "professor" }, { "id": 2, "type": "table", "value": "taughtby" }, { "id": 1, "type": "table", "value": "person" }, { "id": 3, "type": "column", "value": "p_id" }, { "id": 5, "type": "value", "value": "1" }, { "id": 7, "type": "value", "value": "0" } ]
[ { "entity_id": 0, "token_idxs": [ 1 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 3, 4 ] }, { "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", "B-COLUMN", "O", "B-TABLE", "I-TABLE", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O" ]
183
regional_sales
bird:train.json:2704
Which regions have online sales channels that have the most discounts?
SELECT T2.Region FROM `Sales Orders` AS T1 INNER JOIN `Sales Team` AS T2 ON T2.SalesTeamID = T1._SalesTeamID WHERE T1.`Sales Channel` = 'Online' ORDER BY T1.`Discount Applied` DESC LIMIT 1
[ "Which", "regions", "have", "online", "sales", "channels", "that", "have", "the", "most", "discounts", "?" ]
[ { "id": 5, "type": "column", "value": "Discount Applied" }, { "id": 3, "type": "column", "value": "Sales Channel" }, { "id": 1, "type": "table", "value": "Sales Orders" }, { "id": 7, "type": "column", "value": "_salesteamid" }, { "id": 6, "type": "column", "value": "salesteamid" }, { "id": 2, "type": "table", "value": "Sales Team" }, { "id": 0, "type": "column", "value": "region" }, { "id": 4, "type": "value", "value": "Online" } ]
[ { "entity_id": 0, "token_idxs": [ 1 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [ 4 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 3 ] }, { "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", "B-COLUMN", "O", "B-VALUE", "B-TABLE", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "O" ]
184
works_cycles
bird:train.json:7157
For the document Control Assistant who was born on 1975/12/25, how many private documents did he/she have?
SELECT COUNT(T2.BusinessEntityID) FROM Document AS T1 INNER JOIN Employee AS T2 ON T1.Owner = T2.BusinessEntityID WHERE T2.JobTitle = 'Document Control Assistant' AND T2.BirthDate = '1975-12-25' AND T1.DocumentSummary IS NULL
[ "For", "the", "document", "Control", "Assistant", "who", "was", "born", "on", "1975/12/25", ",", "how", "many", "private", "documents", "did", "he", "/", "she", "have", "?" ]
[ { "id": 5, "type": "value", "value": "Document Control Assistant" }, { "id": 2, "type": "column", "value": "businessentityid" }, { "id": 8, "type": "column", "value": "documentsummary" }, { "id": 7, "type": "value", "value": "1975-12-25" }, { "id": 6, "type": "column", "value": "birthdate" }, { "id": 0, "type": "table", "value": "document" }, { "id": 1, "type": "table", "value": "employee" }, { "id": 4, "type": "column", "value": "jobtitle" }, { "id": 3, "type": "column", "value": "owner" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 3, 4 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 9 ] }, { "entity_id": 8, "token_idxs": [ 14 ] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "B-VALUE", "I-VALUE", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O" ]
185
club_1
spider:train_spider.json:4280
What is the description of the club named "Tennis Club"?
SELECT clubdesc FROM club WHERE clubname = "Tennis Club"
[ "What", "is", "the", "description", "of", "the", "club", "named", "\"", "Tennis", "Club", "\"", "?" ]
[ { "id": 3, "type": "column", "value": "Tennis Club" }, { "id": 1, "type": "column", "value": "clubdesc" }, { "id": 2, "type": "column", "value": "clubname" }, { "id": 0, "type": "table", "value": "club" } ]
[ { "entity_id": 0, "token_idxs": [ 10 ] }, { "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": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "B-TABLE", "O", "O" ]
186
university_basketball
spider:train_spider.json:999
What is the total and minimum enrollment of all schools?
SELECT sum(enrollment) , min(enrollment) FROM university
[ "What", "is", "the", "total", "and", "minimum", "enrollment", "of", "all", "schools", "?" ]
[ { "id": 0, "type": "table", "value": "university" }, { "id": 1, "type": "column", "value": "enrollment" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O" ]
187
retails
bird:train.json:6834
What are the top 5 nations of suppliers with the lowest account balance?
SELECT T2.n_name FROM supplier AS T1 INNER JOIN nation AS T2 ON T1.s_nationkey = T2.n_nationkey ORDER BY T1.s_acctbal LIMIT 1
[ "What", "are", "the", "top", "5", "nations", "of", "suppliers", "with", "the", "lowest", "account", "balance", "?" ]
[ { "id": 4, "type": "column", "value": "s_nationkey" }, { "id": 5, "type": "column", "value": "n_nationkey" }, { "id": 3, "type": "column", "value": "s_acctbal" }, { "id": 1, "type": "table", "value": "supplier" }, { "id": 0, "type": "column", "value": "n_name" }, { "id": 2, "type": "table", "value": "nation" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 7 ] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [ 11, 12 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-TABLE", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
189
university_basketball
spider:train_spider.json:1012
What are the names of teams from universities that have a below average enrollment?
SELECT t2.team_name FROM university AS t1 JOIN basketball_match AS t2 ON t1.school_id = t2.school_id WHERE enrollment < (SELECT avg(enrollment) FROM university)
[ "What", "are", "the", "names", "of", "teams", "from", "universities", "that", "have", "a", "below", "average", "enrollment", "?" ]
[ { "id": 2, "type": "table", "value": "basketball_match" }, { "id": 1, "type": "table", "value": "university" }, { "id": 3, "type": "column", "value": "enrollment" }, { "id": 0, "type": "column", "value": "team_name" }, { "id": 4, "type": "column", "value": "school_id" } ]
[ { "entity_id": 0, "token_idxs": [ 2, 3 ] }, { "entity_id": 1, "token_idxs": [ 7 ] }, { "entity_id": 2, "token_idxs": [] }, { "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", "I-COLUMN", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
190
club_1
spider:train_spider.json:4297
Find the first name and last name for the "CTO" of the club "Hopkins Student Enterprises"?
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 = "Hopkins Student Enterprises" AND t2.position = "CTO"
[ "Find", "the", "first", "name", "and", "last", "name", "for", "the", "\"", "CTO", "\"", "of", "the", "club", "\"", "Hopkins", "Student", "Enterprises", "\"", "?" ]
[ { "id": 7, "type": "column", "value": "Hopkins Student Enterprises" }, { "id": 4, "type": "table", "value": "member_of_club" }, { "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" }, { "id": 9, "type": "column", "value": "CTO" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 14 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 17 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 16, 18 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [ 10 ] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "B-COLUMN", "B-COLUMN", "O", "O" ]
191
toxicology
bird:dev.json:339
List the atom ID of the carcinogenic molecule that contains oxygen?
SELECT T1.atom_id FROM atom AS T1 INNER JOIN molecule AS T2 ON T1.molecule_id = T2.molecule_id WHERE T1.element = 'o' AND T2.label = '+'
[ "List", "the", "atom", "ID", "of", "the", "carcinogenic", "molecule", "that", "contains", "oxygen", "?" ]
[ { "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": "o" }, { "id": 7, "type": "value", "value": "+" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 4 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "B-COLUMN", "B-VALUE", "O", "O", "B-TABLE", "O", "O", "O", "O" ]
192
college_1
spider:train_spider.json:3277
What is the last name and office of the professor from the history department?
SELECT T1.emp_lname , T2.prof_office FROM employee AS T1 JOIN professor AS T2 ON T1.emp_num = T2.emp_num JOIN department AS T3 ON T2.dept_code = T3.dept_code WHERE T3.dept_name = 'History'
[ "What", "is", "the", "last", "name", "and", "office", "of", "the", "professor", "from", "the", "history", "department", "?" ]
[ { "id": 1, "type": "column", "value": "prof_office" }, { "id": 2, "type": "table", "value": "department" }, { "id": 0, "type": "column", "value": "emp_lname" }, { "id": 3, "type": "column", "value": "dept_name" }, { "id": 6, "type": "table", "value": "professor" }, { "id": 7, "type": "column", "value": "dept_code" }, { "id": 5, "type": "table", "value": "employee" }, { "id": 4, "type": "value", "value": "History" }, { "id": 8, "type": "column", "value": "emp_num" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 13 ] }, { "entity_id": 4, "token_idxs": [ 12 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 9 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
193
works_cycles
bird:train.json:7014
List down the product name, reviewer name, rating and comments for product under the road line.
SELECT T1.Name, T2.ReviewerName, T2.Rating, T2.Comments FROM Product AS T1 INNER JOIN ProductReview AS T2 USING (productID) WHERE T1.ProductLine = 'R'
[ "List", "down", "the", "product", "name", ",", "reviewer", "name", ",", "rating", "and", "comments", "for", "product", "under", "the", "road", "line", "." ]
[ { "id": 5, "type": "table", "value": "productreview" }, { "id": 1, "type": "column", "value": "reviewername" }, { "id": 6, "type": "column", "value": "productline" }, { "id": 3, "type": "column", "value": "comments" }, { "id": 4, "type": "table", "value": "product" }, { "id": 2, "type": "column", "value": "rating" }, { "id": 0, "type": "column", "value": "name" }, { "id": 7, "type": "value", "value": "R" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 6, 7 ] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "entity_id": 3, "token_idxs": [ 11 ] }, { "entity_id": 4, "token_idxs": [ 3 ] }, { "entity_id": 5, "token_idxs": [ 5 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-TABLE", "B-COLUMN", "B-TABLE", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O" ]
194
thrombosis_prediction
bird:dev.json:1304
Among the patients with a normal blood glucose, how many of them don't have thrombosis?
SELECT COUNT(T1.ID) FROM Patient AS T1 INNER JOIN Laboratory AS T2 ON T1.ID = T2.ID INNER JOIN Examination AS T3 ON T1.ID = T3.ID WHERE T2.GLU < 180 AND T3.Thrombosis = 0
[ "Among", "the", "patients", "with", "a", "normal", "blood", "glucose", ",", "how", "many", "of", "them", "do", "n't", "have", "thrombosis", "?" ]
[ { "id": 0, "type": "table", "value": "examination" }, { "id": 3, "type": "table", "value": "laboratory" }, { "id": 6, "type": "column", "value": "thrombosis" }, { "id": 2, "type": "table", "value": "patient" }, { "id": 4, "type": "column", "value": "glu" }, { "id": 5, "type": "value", "value": "180" }, { "id": 1, "type": "column", "value": "id" }, { "id": 7, "type": "value", "value": "0" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 2 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 7 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 16 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
195
card_games
bird:dev.json:362
What is the description about the ruling of card "Condemn"?
SELECT T2.text FROM cards AS T1 INNER JOIN rulings AS T2 ON T1.uuid = T2.uuid WHERE T1.name = 'Condemn'
[ "What", "is", "the", "description", "about", "the", "ruling", "of", "card", "\"", "Condemn", "\"", "?" ]
[ { "id": 2, "type": "table", "value": "rulings" }, { "id": 4, "type": "value", "value": "Condemn" }, { "id": 1, "type": "table", "value": "cards" }, { "id": 0, "type": "column", "value": "text" }, { "id": 3, "type": "column", "value": "name" }, { "id": 5, "type": "column", "value": "uuid" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 8 ] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 10 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "B-TABLE", "O", "B-VALUE", "O", "O" ]
196
hr_1
spider:train_spider.json:3471
return the smallest salary for every departments.
SELECT MIN(salary) , department_id FROM employees GROUP BY department_id
[ "return", "the", "smallest", "salary", "for", "every", "departments", "." ]
[ { "id": 1, "type": "column", "value": "department_id" }, { "id": 0, "type": "table", "value": "employees" }, { "id": 2, "type": "column", "value": "salary" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [ 3 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O" ]
197
college_3
spider:train_spider.json:4669
Find the first names of faculties of rank Professor in alphabetic order.
SELECT Fname FROM FACULTY WHERE Rank = "Professor" ORDER BY Fname
[ "Find", "the", "first", "names", "of", "faculties", "of", "rank", "Professor", "in", "alphabetic", "order", "." ]
[ { "id": 3, "type": "column", "value": "Professor" }, { "id": 0, "type": "table", "value": "faculty" }, { "id": 1, "type": "column", "value": "fname" }, { "id": 2, "type": "column", "value": "rank" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "B-COLUMN", "B-COLUMN", "O", "O", "O", "O" ]
198
retail_world
bird:train.json:6664
When was the employee who handled order id 10281 hired?
SELECT T1.HireDate FROM Employees AS T1 INNER JOIN Orders AS T2 ON T1.EmployeeID = T2.EmployeeID WHERE T2.OrderID = 10281
[ "When", "was", "the", "employee", "who", "handled", "order", "i", "d", "10281", "hired", "?" ]
[ { "id": 5, "type": "column", "value": "employeeid" }, { "id": 1, "type": "table", "value": "employees" }, { "id": 0, "type": "column", "value": "hiredate" }, { "id": 3, "type": "column", "value": "orderid" }, { "id": 2, "type": "table", "value": "orders" }, { "id": 4, "type": "value", "value": "10281" } ]
[ { "entity_id": 0, "token_idxs": [ 10 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [ 7, 8 ] }, { "entity_id": 4, "token_idxs": [ 9 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-TABLE", "O", "O", "B-TABLE", "B-COLUMN", "I-COLUMN", "B-VALUE", "B-COLUMN", "O" ]
199
synthea
bird:train.json:1540
Who is the patient with a body weight of 61.97 kg?
SELECT T2.first, T2.last FROM observations AS T1 INNER JOIN patients AS T2 ON T1.PATIENT = T2.patient WHERE T1.DESCRIPTION = 'Body Weight' AND T1.UNITS = 'kg' AND T1.VALUE = 61.97
[ "Who", "is", "the", "patient", "with", "a", "body", "weight", "of", "61.97", "kg", "?" ]
[ { "id": 2, "type": "table", "value": "observations" }, { "id": 5, "type": "column", "value": "description" }, { "id": 6, "type": "value", "value": "Body Weight" }, { "id": 3, "type": "table", "value": "patients" }, { "id": 4, "type": "column", "value": "patient" }, { "id": 0, "type": "column", "value": "first" }, { "id": 7, "type": "column", "value": "units" }, { "id": 9, "type": "column", "value": "value" }, { "id": 10, "type": "value", "value": "61.97" }, { "id": 1, "type": "column", "value": "last" }, { "id": 8, "type": "value", "value": "kg" } ]
[ { "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": [ 3 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 6, 7 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [ 10 ] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [ 9 ] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "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", "I-VALUE", "O", "B-VALUE", "B-VALUE", "O" ]
200
mountain_photos
spider:train_spider.json:3723
How many distinct kinds of camera lenses are used to take photos of mountains in the country 'Ethiopia'?
SELECT count(DISTINCT T2.camera_lens_id) FROM mountain AS T1 JOIN photos AS T2 ON T1.id = T2.mountain_id WHERE T1.country = 'Ethiopia'
[ "How", "many", "distinct", "kinds", "of", "camera", "lenses", "are", "used", "to", "take", "photos", "of", "mountains", "in", "the", "country", "'", "Ethiopia", "'", "?" ]
[ { "id": 4, "type": "column", "value": "camera_lens_id" }, { "id": 6, "type": "column", "value": "mountain_id" }, { "id": 0, "type": "table", "value": "mountain" }, { "id": 3, "type": "value", "value": "Ethiopia" }, { "id": 2, "type": "column", "value": "country" }, { "id": 1, "type": "table", "value": "photos" }, { "id": 5, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [ 13 ] }, { "entity_id": 1, "token_idxs": [ 11 ] }, { "entity_id": 2, "token_idxs": [ 16 ] }, { "entity_id": 3, "token_idxs": [ 18 ] }, { "entity_id": 4, "token_idxs": [ 5, 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", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-TABLE", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "B-VALUE", "O", "O" ]
201
regional_sales
bird:train.json:2697
What percentage of sell orders on 04/04/2020 were for the state of New York?
SELECT CAST(SUM(CASE WHEN T2.State = 'New York' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.OrderNumber) FROM `Sales Orders` AS T1 INNER JOIN `Store Locations` AS T2 ON T2.StoreID = T1._StoreID WHERE T1.OrderDate = '4/4/20'
[ "What", "percentage", "of", "sell", "orders", "on", "04/04/2020", "were", "for", "the", "state", "of", "New", "York", "?" ]
[ { "id": 1, "type": "table", "value": "Store Locations" }, { "id": 0, "type": "table", "value": "Sales Orders" }, { "id": 7, "type": "column", "value": "ordernumber" }, { "id": 2, "type": "column", "value": "orderdate" }, { "id": 5, "type": "column", "value": "_storeid" }, { "id": 11, "type": "value", "value": "New York" }, { "id": 4, "type": "column", "value": "storeid" }, { "id": 3, "type": "value", "value": "4/4/20" }, { "id": 10, "type": "column", "value": "state" }, { "id": 6, "type": "value", "value": "100" }, { "id": 8, "type": "value", "value": "0" }, { "id": 9, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 4 ] }, { "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": [ 5 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [ 10 ] }, { "entity_id": 11, "token_idxs": [ 12, 13 ] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-TABLE", "B-COLUMN", "B-COLUMN", "B-VALUE", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "I-VALUE", "O" ]
202
movielens
bird:train.json:2286
How many distinct movies in English stars a male actor who acts the best?
SELECT COUNT(DISTINCT T1.actorid) FROM actors AS T1 INNER JOIN movies2actors AS T2 ON T1.actorid = T2.actorid INNER JOIN movies AS T3 ON T2.movieid = T3.movieid WHERE T3.isEnglish = 'T' AND T1.a_gender = 'M' AND T1.a_quality = 5
[ "How", "many", "distinct", "movies", "in", "English", "stars", "a", "male", "actor", "who", "acts", "the", "best", "?" ]
[ { "id": 3, "type": "table", "value": "movies2actors" }, { "id": 5, "type": "column", "value": "isenglish" }, { "id": 9, "type": "column", "value": "a_quality" }, { "id": 7, "type": "column", "value": "a_gender" }, { "id": 1, "type": "column", "value": "actorid" }, { "id": 4, "type": "column", "value": "movieid" }, { "id": 0, "type": "table", "value": "movies" }, { "id": 2, "type": "table", "value": "actors" }, { "id": 6, "type": "value", "value": "T" }, { "id": 8, "type": "value", "value": "M" }, { "id": 10, "type": "value", "value": "5" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 5 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O" ]
203
mondial_geo
bird:train.json:8460
What is the full name of ABEDA and when was it established?
SELECT Name, Established FROM organization WHERE Abbreviation = 'ABEDA'
[ "What", "is", "the", "full", "name", "of", "ABEDA", "and", "when", "was", "it", "established", "?" ]
[ { "id": 0, "type": "table", "value": "organization" }, { "id": 3, "type": "column", "value": "abbreviation" }, { "id": 2, "type": "column", "value": "established" }, { "id": 4, "type": "value", "value": "ABEDA" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [ 11 ] }, { "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", "O", "B-COLUMN", "O", "B-VALUE", "O", "O", "O", "O", "B-COLUMN", "O" ]
204
movie_3
bird:train.json:9243
List the address in Texas in the ascending order of city id.
SELECT address FROM address WHERE district = 'Texas' AND city_id = ( SELECT MIN(city_id) FROM address WHERE district = 'Texas' )
[ "List", "the", "address", "in", "Texas", "in", "the", "ascending", "order", "of", "city", "i", "d." ]
[ { "id": 2, "type": "column", "value": "district" }, { "id": 0, "type": "table", "value": "address" }, { "id": 1, "type": "column", "value": "address" }, { "id": 4, "type": "column", "value": "city_id" }, { "id": 3, "type": "value", "value": "Texas" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 4 ] }, { "entity_id": 4, "token_idxs": [ 10, 11, 12 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-VALUE", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN" ]
205
customers_card_transactions
spider:train_spider.json:739
Show the card type codes and the number of transactions.
SELECT T2.card_type_code , count(*) FROM Financial_transactions AS T1 JOIN Customers_cards AS T2 ON T1.card_id = T2.card_id GROUP BY T2.card_type_code
[ "Show", "the", "card", "type", "codes", "and", "the", "number", "of", "transactions", "." ]
[ { "id": 1, "type": "table", "value": "financial_transactions" }, { "id": 2, "type": "table", "value": "customers_cards" }, { "id": 0, "type": "column", "value": "card_type_code" }, { "id": 3, "type": "column", "value": "card_id" } ]
[ { "entity_id": 0, "token_idxs": [ 3, 4 ] }, { "entity_id": 1, "token_idxs": [ 9 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 2 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-TABLE", "O" ]
206
icfp_1
spider:train_spider.json:2874
Who belong to the institution "University of Oxford"? Show the first names and last names.
SELECT DISTINCT t1.fname , t1.lname FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN inst AS t3 ON t2.instid = t3.instid WHERE t3.name = "University of Oxford"
[ "Who", "belong", "to", "the", "institution", "\"", "University", "of", "Oxford", "\"", "?", "Show", "the", "first", "names", "and", "last", "names", "." ]
[ { "id": 4, "type": "column", "value": "University of Oxford" }, { "id": 6, "type": "table", "value": "authorship" }, { "id": 5, "type": "table", "value": "authors" }, { "id": 7, "type": "column", "value": "instid" }, { "id": 8, "type": "column", "value": "authid" }, { "id": 0, "type": "column", "value": "fname" }, { "id": 1, "type": "column", "value": "lname" }, { "id": 2, "type": "table", "value": "inst" }, { "id": 3, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 14 ] }, { "entity_id": 2, "token_idxs": [ 13 ] }, { "entity_id": 3, "token_idxs": [ 17 ] }, { "entity_id": 4, "token_idxs": [ 6, 7, 8 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "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", "O", "O", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "B-COLUMN", "O" ]
207
cre_Doc_Tracking_DB
spider:train_spider.json:4242
Show the ids of all employees who have authorized destruction.
SELECT DISTINCT Destruction_Authorised_by_Employee_ID FROM Documents_to_be_destroyed
[ "Show", "the", "ids", "of", "all", "employees", "who", "have", "authorized", "destruction", "." ]
[ { "id": 1, "type": "column", "value": "destruction_authorised_by_employee_id" }, { "id": 0, "type": "table", "value": "documents_to_be_destroyed" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
208
image_and_language
bird:train.json:7583
What is the image ID with a predicted class of "parked on"?
SELECT DISTINCT T1.IMG_ID FROM IMG_REL AS T1 INNER JOIN PRED_CLASSES AS T2 ON T1.PRED_CLASS_ID = T2.PRED_CLASS_ID WHERE T2.PRED_CLASS = 'parked on'
[ "What", "is", "the", "image", "ID", "with", "a", "predicted", "class", "of", "\"", "parked", "on", "\"", "?" ]
[ { "id": 5, "type": "column", "value": "pred_class_id" }, { "id": 2, "type": "table", "value": "pred_classes" }, { "id": 3, "type": "column", "value": "pred_class" }, { "id": 4, "type": "value", "value": "parked on" }, { "id": 1, "type": "table", "value": "img_rel" }, { "id": 0, "type": "column", "value": "img_id" } ]
[ { "entity_id": 0, "token_idxs": [ 3, 4 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 7, 8 ] }, { "entity_id": 4, "token_idxs": [ 11, 12 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-VALUE", "I-VALUE", "O", "O" ]
209
cookbook
bird:train.json:8891
How many ingredients are there in Apricot Yogurt Parfaits?
SELECT COUNT(*) FROM Recipe AS T1 INNER JOIN Quantity AS T2 ON T1.recipe_id = T2.recipe_id WHERE T1.title = 'Apricot Yogurt Parfaits'
[ "How", "many", "ingredients", "are", "there", "in", "Apricot", "Yogurt", "Parfaits", "?" ]
[ { "id": 3, "type": "value", "value": "Apricot Yogurt Parfaits" }, { "id": 4, "type": "column", "value": "recipe_id" }, { "id": 1, "type": "table", "value": "quantity" }, { "id": 0, "type": "table", "value": "recipe" }, { "id": 2, "type": "column", "value": "title" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 6, 7, 8 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "O" ]
210
game_1
spider:train_spider.json:6034
How many different students play games?
SELECT count(DISTINCT StuID) FROM Plays_games
[ "How", "many", "different", "students", "play", "games", "?" ]
[ { "id": 0, "type": "table", "value": "plays_games" }, { "id": 1, "type": "column", "value": "stuid" } ]
[ { "entity_id": 0, "token_idxs": [ 4, 5 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "B-TABLE", "I-TABLE", "O" ]
211
customer_complaints
spider:train_spider.json:5780
What is the phone number of the customer who has filed the most recent complaint?
SELECT t1.phone_number FROM customers AS t1 JOIN complaints AS t2 ON t1.customer_id = t2.customer_id ORDER BY t2.date_complaint_raised DESC LIMIT 1
[ "What", "is", "the", "phone", "number", "of", "the", "customer", "who", "has", "filed", "the", "most", "recent", "complaint", "?" ]
[ { "id": 3, "type": "column", "value": "date_complaint_raised" }, { "id": 0, "type": "column", "value": "phone_number" }, { "id": 4, "type": "column", "value": "customer_id" }, { "id": 2, "type": "table", "value": "complaints" }, { "id": 1, "type": "table", "value": "customers" } ]
[ { "entity_id": 0, "token_idxs": [ 3, 4 ] }, { "entity_id": 1, "token_idxs": [ 7 ] }, { "entity_id": 2, "token_idxs": [ 14 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
212
retail_world
bird:train.json:6384
List the company names of customers from the city with the most customers.
SELECT CompanyName FROM `Customer and Suppliers by City` WHERE CITY = ( SELECT City FROM `Customer and Suppliers by City` GROUP BY City ORDER BY COUNT(Relationship) DESC LIMIT 1 )
[ "List", "the", "company", "names", "of", "customers", "from", "the", "city", "with", "the", "most", "customers", "." ]
[ { "id": 0, "type": "table", "value": "Customer and Suppliers by City" }, { "id": 3, "type": "column", "value": "relationship" }, { "id": 1, "type": "column", "value": "companyname" }, { "id": 2, "type": "column", "value": "city" } ]
[ { "entity_id": 0, "token_idxs": [ 5, 6, 7 ] }, { "entity_id": 1, "token_idxs": [ 2, 3 ] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-TABLE", "I-TABLE", "I-TABLE", "B-COLUMN", "O", "O", "O", "O", "O" ]
213
device
spider:train_spider.json:5079
What are the different software platforms for devices, ordered by frequency descending?
SELECT Software_Platform FROM device GROUP BY Software_Platform ORDER BY COUNT(*) DESC
[ "What", "are", "the", "different", "software", "platforms", "for", "devices", ",", "ordered", "by", "frequency", "descending", "?" ]
[ { "id": 1, "type": "column", "value": "software_platform" }, { "id": 0, "type": "table", "value": "device" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [ 4, 5 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "O", "O" ]
214
works_cycles
bird:train.json:7182
What are the total per assembly quantity for unit measure code EA, IN and OZ respectively? What are the name of these 3 code?
SELECT SUM(T1.PerAssemblyQty), T2.Name FROM BillOfMaterials AS T1 INNER JOIN UnitMeasure AS T2 ON T1.UnitMeasureCode = T2.UnitMeasureCode WHERE T1.UnitMeasureCode IN ('EA', 'IN', 'OZ') GROUP BY T2.Name
[ "What", "are", "the", "total", "per", "assembly", "quantity", "for", "unit", "measure", "code", "EA", ",", "IN", "and", "OZ", "respectively", "?", "What", "are", "the", "name", "of", "these", "3", "code", "?" ]
[ { "id": 1, "type": "table", "value": "billofmaterials" }, { "id": 3, "type": "column", "value": "unitmeasurecode" }, { "id": 7, "type": "column", "value": "perassemblyqty" }, { "id": 2, "type": "table", "value": "unitmeasure" }, { "id": 0, "type": "column", "value": "name" }, { "id": 4, "type": "value", "value": "EA" }, { "id": 5, "type": "value", "value": "IN" }, { "id": 6, "type": "value", "value": "OZ" } ]
[ { "entity_id": 0, "token_idxs": [ 21 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 8, 9 ] }, { "entity_id": 3, "token_idxs": [ 10 ] }, { "entity_id": 4, "token_idxs": [ 11 ] }, { "entity_id": 5, "token_idxs": [ 13 ] }, { "entity_id": 6, "token_idxs": [ 15 ] }, { "entity_id": 7, "token_idxs": [ 4, 5 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "I-TABLE", "B-COLUMN", "B-VALUE", "O", "B-VALUE", "O", "B-VALUE", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O" ]
215
insurance_and_eClaims
spider:train_spider.json:1508
Sort the customer names in alphabetical order.
SELECT customer_details FROM customers ORDER BY customer_details
[ "Sort", "the", "customer", "names", "in", "alphabetical", "order", "." ]
[ { "id": 1, "type": "column", "value": "customer_details" }, { "id": 0, "type": "table", "value": "customers" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "O", "O", "O" ]