prompt listlengths 1 1 | data_source stringclasses 1
value | reward_model dict | extra_info dict | schema stringlengths 329 25.8k |
|---|---|---|---|---|
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE lists_users (\n ... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT movie_title FROM movies WHERE movie_release_year = 1945 ORDER BY movie_popularity DESC LIMIT 1"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "released in the year 1945 refers to movie_release_year = 1945;",
"index": 0,
"question": "Name movie titles released in year 1945. Sort the listing by the descending order of movie popularity.",
"question_id": "0",
"split": "train"
} | CREATE TABLE lists_users (
user_id integer, -- example: [2385, 15264]
list_id integer, -- example: [192287, 192313]
PRIMARY KEY (user_id, list_id),
CONSTRAINT fk_lists_users_user_id FOREIGN KEY (user_id) REFERENCES lists (user_id),
CONSTRAINT fk_lists_users_list_id FOREIGN KEY (list_id) REFERENCES l... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE lists (\n use... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT movie_title, movie_release_year, director_name FROM movies ORDER BY movie_popularity DESC LIMIT 1"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "most popular movie refers to MAX(movie_popularity); when it was released refers to movie_release_year; director for the movie refers to director_name;",
"index": 1,
"question": "State the most popular movie? When was it released and who is the direct... | CREATE TABLE lists (
user_id integer, -- example: [88260493, 45204418]
list_id integer, -- example: [1, 2]
list_title text, -- example: ['director', 'the most', 'The most', 'Popular', 'Max', 'Directors']
list_movie_number integer, -- example: [5, 3]
list_update_timestamp_utc text, -- example: ['2019... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE ratings_users (\... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT movie_title, movie_release_year FROM movies ORDER BY LENGTH(movie_popularity) DESC LIMIT 1"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "longest movie title refers to MAX(LENGTH(movie_title)); when it was released refers to movie_release_year;",
"index": 2,
"question": "What is the name of the longest movie title? When was it released?",
"question_id": "2",
"split": "train"
} | CREATE TABLE ratings_users (
user_id integer, -- example: [41579158, 68654088]
user_avatar_image_url text, -- example: ['https://assets.mubicdn.net/images/avatar']
user_cover_image_url text, -- example: ['https://assets.mubicdn.net/images/cover_']
user_eligible_for_trial integer, -- example: [1, 0]
... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE movies (\n mo... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT movie_title FROM movies GROUP BY movie_title ORDER BY COUNT(movie_title) DESC LIMIT 1"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "movie with the most rating refers to MAX(SUM(rating_score));",
"index": 3,
"question": "Name the movie with the most ratings.",
"question_id": "3",
"split": "train"
} | CREATE TABLE movies (
movie_id integer, -- example: [1, 2]
movie_title text, -- example: ['Most', 'Max', 'La Antena', 'Elementary Particles']
movie_release_year integer, -- example: [2007, 2006]
movie_url text, -- example: ['http://mubi.com/films/la-antena', 'http://mubi.com/films/elementary-particl']
... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE lists_users (\n ... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT AVG(movie_popularity) FROM movies WHERE director_name = 'Stanley Kubrick'"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "average = AVG(movie_popularity); number of Mubi users who loves the movie refers to movie_popularity;",
"index": 4,
"question": "What is the average number of Mubi users who love movies directed by Stanley Kubrick?",
"question_id": "4",
"split": ... | CREATE TABLE lists_users (
user_id integer, -- example: [2385, 15264]
list_id integer, -- example: [192287, 192313]
list_creation_date_utc text, -- example: ['2009-12-18', '2010-01-30']
PRIMARY KEY (user_id, list_id),
CONSTRAINT fk_lists_users_user_id FOREIGN KEY (user_id) REFERENCES lists (user_id)... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE lists_users (\n ... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT director_name FROM movies WHERE movie_title = 'Sex, Drink and Bloodshed'"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "Sex, Drink and Bloodshed refers to movie title = 'Sex, Drink and Bloodshed';",
"index": 15,
"question": "Who is the director of the movie Sex, Drink and Bloodshed?",
"question_id": "15",
"split": "train"
} | CREATE TABLE lists_users (
user_id integer, -- example: [2385, 15264]
list_id integer, -- example: [192287, 192313]
list_update_date_utc text, -- example: ['2019-11-26', '2020-05-01']
list_creation_date_utc text, -- example: ['2009-12-18', '2010-01-30']
user_trialist integer, -- example: [1, 0]
... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE ratings_users (\... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT list_title FROM lists ORDER BY list_followers DESC LIMIT 1"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "most followed list refers to MAX(list_followers);",
"index": 16,
"question": "What is the name of the most followed list?",
"question_id": "16",
"split": "train"
} | CREATE TABLE ratings_users (
user_id integer, -- example: [41579158, 68654088]
rating_date_utc text, -- example: ['2017-06-10', '2012-10-02']
user_trialist integer, -- example: [0, 1]
user_subscriber integer, -- example: [0, 1]
CONSTRAINT fk_ratings_users_user_id FOREIGN KEY (user_id) REFERENCES lis... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE ratings (\n m... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT list_url FROM lists WHERE list_update_timestamp_utc LIKE '2012%' AND list_followers BETWEEN 1 AND 2 ORDER BY list_update_timestamp_utc DESC LIMIT 1"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "URL to the list page on Mubi refers to list_url; list_followers = 1 OR list_followers = 2; last update timestamp was on 2012 refers to list_update_timestamp_utc BETWEEN '2012-1-1' AND '2012-12-31';",
"index": 17,
"question": "What are the URL to the ... | CREATE TABLE ratings (
movie_id integer, -- example: [1066, 1067]
rating_id integer, -- example: [15610495, 10704606]
rating_url text, -- example: ['http://mubi.com/films/pavee-lackeen-the-']
rating_score integer, -- example: [3, 2]
rating_timestamp_utc text, -- example: ['2017-06-10 12:38:33', '201... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE ratings_users (\... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT list_id FROM lists_users WHERE user_id = 85981819 ORDER BY list_creation_date_utc ASC LIMIT 1"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "first created list refers to oldest list_creation_date_utc;",
"index": 18,
"question": "What is the list ID that was first created by user 85981819?",
"question_id": "18",
"split": "train"
} | CREATE TABLE ratings_users (
user_id integer, -- example: [41579158, 68654088]
rating_date_utc text, -- example: ['2017-06-10', '2012-10-02']
user_avatar_image_url text, -- example: ['https://assets.mubicdn.net/images/avatar']
user_eligible_for_trial integer, -- example: [1, 0]
CONSTRAINT fk_ratings... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE ratings (\n m... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT movie_title, movie_popularity FROM movies WHERE movie_release_year = 2021 AND director_name = 'Steven Spielberg'"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "movie released in 2021 refers to movie_release_year = 2021; popularity refers to movie_popularity;",
"index": 20,
"question": "What are the movie popularity of the movies released in 2021 that were directed by Steven Spielberg? List the names of the ... | CREATE TABLE ratings (
movie_id integer, -- example: [1066, 1067]
user_id integer, -- example: [41579158, 85981819]
CONSTRAINT fk_ratings_movie_id FOREIGN KEY (movie_id) REFERENCES movies (movie_id),
CONSTRAINT fk_ratings_user_id FOREIGN KEY (user_id) REFERENCES ratings_users (user_id),
CONSTRAINT f... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE lists_users (\n ... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT movie_release_year, director_name FROM movies WHERE movie_release_year IS NOT NULL ORDER BY movie_release_year ASC LIMIT 1"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "first movie refers to oldest movie_release_year;",
"index": 21,
"question": "When was the first movie released and who directed it?",
"question_id": "21",
"split": "train"
} | CREATE TABLE lists_users (
user_id integer, -- example: [2385, 15264]
list_id integer, -- example: [192287, 192313]
PRIMARY KEY (user_id, list_id),
CONSTRAINT fk_lists_users_user_id FOREIGN KEY (user_id) REFERENCES lists (user_id),
CONSTRAINT fk_lists_users_list_id FOREIGN KEY (list_id) REFERENCES l... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE ratings_users (\... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT user_id FROM lists_users WHERE user_subscriber = 1 GROUP BY user_id HAVING MAX(SUBSTR(list_creation_date_utc, 1, 4)) - MIN(SUBSTR(list_creation_date_utc, 1, 4)) >= 10"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "user was a subscriber when he created the list refers to user_subscriber = 1; user who created a list for 10 consecutive years refers to user_id with list_creation_date_utc for 10 succeeding years;",
"index": 22,
"question": "What is the user ID of t... | CREATE TABLE ratings_users (
user_id integer, -- example: [41579158, 68654088]
user_subscriber integer, -- example: [0, 1]
user_avatar_image_url text, -- example: ['https://assets.mubicdn.net/images/avatar']
CONSTRAINT fk_ratings_users_user_id FOREIGN KEY (user_id) REFERENCES lists_users (user_id)
);
C... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE ratings_users (\... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT T2.user_eligible_for_trial, T1.list_followers FROM lists AS T1 INNER JOIN lists_users AS T2 ON T1.user_id = T1.user_id AND T1.list_id = T2.list_id WHERE T1.list_title = 'World War 2 and Kids'"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "user was eligible for trial when he created the list refers to user_eligible_for_trial = 1; number of followers a list have refers to list_followers;",
"index": 24,
"question": "Was the user who created the \"World War 2 and Kids\" list eligible for ... | CREATE TABLE ratings_users (
user_id integer, -- example: [41579158, 68654088]
rating_date_utc text, -- example: ['2017-06-10', '2012-10-02']
user_trialist integer, -- example: [0, 1]
user_subscriber integer, -- example: [0, 1]
user_avatar_image_url text, -- example: ['https://assets.mubicdn.net/ima... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE movies (\n mo... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT T1.list_movie_number, T2.user_has_payment_method FROM lists AS T1 INNER JOIN lists_users AS T2 ON T1.list_id = T2.list_id ORDER BY T1.list_movie_number DESC LIMIT 1"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "list with the most number of movies refers to MAX(list_movie_number); user_has_payment_method = 1 means the user was a paying subscriber when he created the list; user_has_payment_method = 0 means the user was not a paying subscriber when he created the ... | CREATE TABLE movies (
movie_id integer, -- example: [1, 2]
movie_title text, -- example: ['When', 'Most', 'Max', 'A Number', 'Numbers', 'La Antena']
movie_release_year integer, -- example: [2007, 2006]
movie_url text, -- example: ['http://mubi.com/films/la-antena', 'http://mubi.com/films/elementary-part... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE ratings (\n m... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT T1.list_followers, T2.user_subscriber = 1 FROM lists AS T1 INNER JOIN lists_users AS T2 ON T1.user_id = T2.user_id AND T2.list_id = T2.list_id WHERE T2.user_id = 4208563 ORDER BY T1.list_followers DESC LIMIT 1"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "User 4208563 refers to user_id;highest number of followers refers to MAX(list_followers); user_subscriber = 1 means that the user was a subscriber when he created the list; user_subscriber = 0 means the user was not a subscriber when he created the list ... | CREATE TABLE ratings (
movie_id integer, -- example: [1066, 1067]
rating_id integer, -- example: [15610495, 10704606]
rating_url text, -- example: ['http://mubi.com/films/pavee-lackeen-the-']
rating_score integer, -- example: [3, 2]
critic text, -- example: ['Mean', 'how', 'I am a bit disappointed b... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE ratings (\n m... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT AVG(T1.list_movie_number), T2.user_avatar_image_url FROM lists AS T1 INNER JOIN lists_users AS T2 ON T1.list_id = T2.list_id AND T1.user_id = T2.user_id WHERE T2.user_id = 8516503"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "user profile image URL refers to user_avatar_image_url; user 8516503 refers to user_id; Average refers to AVG(list_movie_number where user_id = 8516503)\n\n",
"index": 36,
"question": "What is the average number of movies added to the lists of user 8... | CREATE TABLE ratings (
movie_id integer, -- example: [1066, 1067]
rating_url text, -- example: ['http://mubi.com/films/pavee-lackeen-the-']
rating_timestamp_utc text, -- example: ['2017-06-10 12:38:33', '2014-08-15 23:42:31']
user_id integer, -- example: [41579158, 85981819]
user_subscriber integer,... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE lists_users (\n ... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT T1.list_followers FROM lists AS T1 INNER JOIN lists_users AS T2 ON T1.user_id = T2.user_id AND T1.list_id = T2.list_id WHERE T2.list_creation_date_utc BETWEEN '2016-02-01' AND '2016-02-29' AND T2.user_eligible_for_trial = 1"
},
"style": "rule"
... | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "created a list in the February of 2016 refer to list_creation_date_utc BETWEEN 2/1/2016 and 2/29/2016; eligible for trial refers to user_eligible_for_trial = 1;\n",
"index": 38,
"question": "How many users who created a list in the February of 2016 w... | CREATE TABLE lists_users (
user_id integer, -- example: [2385, 15264]
list_id integer, -- example: [192287, 192313]
list_update_date_utc text, -- example: ['2019-11-26', '2020-05-01']
list_creation_date_utc text, -- example: ['2009-12-18', '2010-01-30']
user_subscriber integer, -- example: [1, 0]
... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE lists (\n use... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT COUNT(*) FROM lists WHERE SUBSTR(list_update_timestamp_utc, 1, 4) - SUBSTR(list_creation_timestamp_utc, 1, 4) > 10"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "updated 10 years after it was created refers to list_update_timestamp_utc > (list_creation_timestamp_utc+10);",
"index": 50,
"question": "How many movie lists were still updated 10 years after it was created?",
"question_id": "50",
"split": "trai... | CREATE TABLE lists (
user_id integer, -- example: [88260493, 45204418]
list_id integer, -- example: [1, 2]
list_movie_number integer, -- example: [5, 3]
list_update_timestamp_utc text, -- example: ['2019-01-24 19:16:18', '2018-12-03 15:12:20']
list_creation_timestamp_utc text, -- example: ['2009-11-... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE ratings (\n m... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT list_description FROM lists WHERE list_title = 'Short and pretty damn sweet'"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "Short and pretty damn sweet is list_title; description refers to list_description;",
"index": 51,
"question": "What's the description for the movie list \"Short and pretty damn sweet\"?",
"question_id": "51",
"split": "train"
} | CREATE TABLE ratings (
movie_id integer, -- example: [1066, 1067]
rating_id integer, -- example: [15610495, 10704606]
rating_score integer, -- example: [3, 2]
rating_timestamp_utc text, -- example: ['2017-06-10 12:38:33', '2014-08-15 23:42:31']
critic text, -- example: ['I am a bit disappointed by t... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE lists_users (\n ... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT list_url FROM lists WHERE list_title = 'Short and pretty damn sweet'"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "Short and pretty damn sweet is list_title; location of the movie refers to list_url;",
"index": 52,
"question": "Where can I find the movie list \"Short and pretty damn sweet\"?",
"question_id": "52",
"split": "train"
} | CREATE TABLE lists_users (
user_id integer, -- example: [2385, 15264]
list_id integer, -- example: [192287, 192313]
list_creation_date_utc text, -- example: ['2009-12-18', '2010-01-30']
user_subscriber integer, -- example: [1, 0]
user_avatar_image_url text, -- example: ['https://assets.mubicdn.net/i... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE ratings_users (\... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT COUNT(*) FROM lists WHERE list_followers > 200 AND list_update_timestamp_utc > '2010-01-01'"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "created after 2010/1/1 refers to list_update_timestamp_utc>'2010/1/1'; over 200 followers refers to list_followers>200;",
"index": 53,
"question": "Among the movie lists created after 2010/1/1, how many of them have over 200 followers?",
"question_... | CREATE TABLE ratings_users (
user_id integer, -- example: [41579158, 68654088]
rating_date_utc text, -- example: ['2017-06-10', '2012-10-02']
user_trialist integer, -- example: [0, 1]
user_subscriber integer, -- example: [0, 1]
user_avatar_image_url text, -- example: ['https://assets.mubicdn.net/ima... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE movies (\n mo... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT COUNT(*) FROM lists_users WHERE user_id = 83373278 AND user_subscriber = 1"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "the user was a subscriber when he created the list refers to user_subscriber = 1; user 83373278 refers to user_id = 83373278;",
"index": 54,
"question": "How many movie lists were created by user 83373278 when he or she was a subscriber?",
"questio... | CREATE TABLE movies (
movie_id integer, -- example: [1, 2]
movie_title_language text, -- example: ['en']
PRIMARY KEY (movie_id)
);
CREATE TABLE lists (
user_id integer, -- example: [88260493, 45204418]
list_id integer, -- example: [1, 2]
list_title text, -- example: ['movie list', 'Movie List',... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE movies (\n mo... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT movie_release_year FROM movies WHERE movie_title = 'La Antena'"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "movie La Antena refers to movie_title = 'La Antena'; which year refers to movie_release_year;",
"index": 55,
"question": "In which year was the movie \"La Antena\" released?",
"question_id": "55",
"split": "train"
} | CREATE TABLE movies (
movie_id integer, -- example: [1, 2]
movie_title text, -- example: ['La Antena', 'Release', 'Elementary Particles']
movie_release_year integer, -- example: [2007, 2006]
movie_title_language text, -- example: ['en']
movie_popularity integer, -- example: [105, 23]
movie_image... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE lists (\n use... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT movie_url FROM movies WHERE movie_title = 'La Antena'"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "movie La Antena refers to movie_title = 'La Antena'; url refers to movie_url;",
"index": 56,
"question": "Please give me the url of the movie \"La Antena\".",
"question_id": "56",
"split": "train"
} | CREATE TABLE lists (
user_id integer, -- example: [88260493, 45204418]
list_id integer, -- example: [1, 2]
list_movie_number integer, -- example: [5, 3]
list_update_timestamp_utc text, -- example: ['2019-01-24 19:16:18', '2018-12-03 15:12:20']
list_followers integer, -- example: [5, 1]
list_url ... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE lists_users (\n ... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT movie_title FROM movies WHERE movie_title = 'The General' OR movie_title = 'Il grido' ORDER BY movie_popularity DESC LIMIT 1"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "The General and Il grido are movie_title; more popular movie refers to higher (movie_popularity);",
"index": 57,
"question": "Which movie is more popular, \"The General\" or \"Il grido\"?",
"question_id": "57",
"split": "train"
} | CREATE TABLE lists_users (
user_id integer, -- example: [2385, 15264]
list_id integer, -- example: [192287, 192313]
list_creation_date_utc text, -- example: ['2009-12-18', '2010-01-30']
user_trialist integer, -- example: [1, 0]
user_eligible_for_trial text, -- example: ['0', '1']
PRIMARY KEY (us... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE movies (\n mo... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT COUNT(movie_id) FROM movies WHERE director_name = 'Hong Sang-soo'"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "Hong Sang-soo is the name of director;",
"index": 58,
"question": "How many movies registered on Mubi are directed by Hong Sang-soo?",
"question_id": "58",
"split": "train"
} | CREATE TABLE movies (
movie_id integer, -- example: [1, 2]
director_id text, -- example: ['131', '73']
director_name text, -- example: ['Hong Sang-soo', 'Esteban Sapir', 'Oskar Roehler']
director_url text, -- example: ['http://mubi.com/cast/esteban-sapir', 'http://mubi.com/cast/oskar-roehler']
PRIMA... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE ratings (\n m... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT T2.user_trialist FROM lists AS T1 INNER JOIN lists_users AS T2 ON T1.list_id = T2.list_id AND T1.user_id = T2.user_id WHERE T1.list_title = '250 Favourite Films'"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "the user was a trialist when he created the list refers to user_trailist = 1; 250 Favourite Films is list_title;",
"index": 59,
"question": "Was the user who created the list \"250 Favourite Films\" a trialist when he or she created the list?",
"qu... | CREATE TABLE ratings (
movie_id integer, -- example: [1066, 1067]
user_id integer, -- example: [41579158, 85981819]
user_trialist integer, -- example: [0, 1]
user_subscriber integer, -- example: [0, 1]
user_has_payment_method integer, -- example: [0, 1]
CONSTRAINT fk_ratings_movie_id FOREIGN KEY... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE lists (\n use... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT T1.list_title FROM lists AS T1 INNER JOIN lists_users AS T2 ON T1.list_id = T2.list_id AND T1.user_id = T2.user_id WHERE T1.user_id = 32172230 AND T2.user_eligible_for_trial = 1"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "the user was eligible for trail when he created the list refers to user_eligile_for_trail = 1; user 32172230 refers to user_id = 32172230;",
"index": 60,
"question": "Please list the titles of the movie lists user 32172230 created when he or she was ... | CREATE TABLE lists (
user_id integer, -- example: [88260493, 45204418]
list_id integer, -- example: [1, 2]
list_title text, -- example: ['The Movie List', 'movie list', 'Movie List', 'please', 'create', 'Title']
list_movie_number integer, -- example: [5, 3]
list_creation_timestamp_utc text, -- examp... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE lists_users (\n ... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT COUNT(*) FROM lists AS T1 INNER JOIN lists_users AS T2 ON T1.list_id = T2.list_id AND T1.user_id = T2.user_id WHERE T1.user_id = 85981819 AND T1.list_movie_number > 100 AND T2.user_has_payment_method = 1"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "the user was a paying subscriber when he created the list refers to user_has_payment_method = 1; movie lists with over 100 refers to list_movie_number >100; user 85981819 refers to user_id = 85981819;",
"index": 61,
"question": "How many movie list... | CREATE TABLE lists_users (
user_id integer, -- example: [2385, 15264]
list_id integer, -- example: [192287, 192313]
list_creation_date_utc text, -- example: ['2009-12-18', '2010-01-30']
user_trialist integer, -- example: [1, 0]
user_avatar_image_url text, -- example: ['https://assets.mubicdn.net/ima... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE lists_users (\n ... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT T1.list_description FROM lists AS T1 INNER JOIN lists_users AS T2 ON T1.list_id = T2.list_id AND T1.user_id = T2.user_id WHERE T1.user_id = 85981819 ORDER BY T1.list_followers DESC LIMIT 1"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "user 85981819 refers to user_id = 85981819; most followers refers to Max(list_followers); description refers to list_descriptions;",
"index": 62,
"question": "What's the description of user 85981819's movie list with the most followers?",
"question... | CREATE TABLE lists_users (
user_id integer, -- example: [2385, 15264]
list_id integer, -- example: [192287, 192313]
list_update_date_utc text, -- example: ['2019-11-26', '2020-05-01']
user_trialist integer, -- example: [1, 0]
user_subscriber integer, -- example: [1, 0]
user_avatar_image_url text... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE ratings (\n m... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT T2.list_update_date_utc FROM lists AS T1 INNER JOIN lists_users AS T2 ON T1.list_id = T2.list_id AND T1.user_id = T2.user_id WHERE T1.list_title = '250 Favourite Films' ORDER BY T2.list_update_date_utc DESC LIMIT 1"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "250 Favourite Films refers to list_title; last update refers to list_update_date_utc;",
"index": 63,
"question": "When did the creator of the list \"250 Favourite Films\" last updated a movie list?",
"question_id": "63",
"split": "train"
} | CREATE TABLE ratings (
movie_id integer, -- example: [1066, 1067]
rating_id integer, -- example: [15610495, 10704606]
rating_url text, -- example: ['http://mubi.com/films/pavee-lackeen-the-']
critic_comments integer, -- example: [0, 2]
user_id integer, -- example: [41579158, 85981819]
user_eligi... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE movies (\n mo... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT T2.user_avatar_image_url FROM lists AS T1 INNER JOIN lists_users AS T2 ON T1.list_id = T2.list_id AND T1.user_id = T2.user_id WHERE T1.list_title = '250 Favourite Films'"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "250 Favourite Films refers to list_title; avatar image refers to user_avatar_image_url;",
"index": 64,
"question": "What's the avatar image of the user who created the movie list \"250 Favourite Films\"?",
"question_id": "64",
"split": "train"
} | CREATE TABLE movies (
movie_id integer, -- example: [1, 2]
movie_title text, -- example: ['Avatar', 'Image', 'Avatar 3', 'La Antena', 'Elementary Particles']
movie_release_year integer, -- example: [2007, 2006]
movie_url text, -- example: ['http://mubi.com/films/la-antena', 'http://mubi.com/films/elemen... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE lists (\n use... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT COUNT(list_id) FROM lists_users WHERE user_id = ( SELECT user_id FROM lists WHERE list_title = '250 Favourite Films' )"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "250 Favourite Films refers to list_title;",
"index": 65,
"question": "How many more movie lists were created by the user who created the movie list \"250 Favourite Films\"?",
"question_id": "65",
"split": "train"
} | CREATE TABLE lists (
user_id integer, -- example: [88260493, 45204418]
list_id integer, -- example: [1, 2]
list_title text, -- example: ['250 Favourite Films', 'Favourite Films ', 'Favourite films', 'Favourite FILMS', 'Favourite fiLms', 'FAVOURITE FILMS']
list_update_timestamp_utc text, -- example: ['20... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE lists_users (\n ... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT director_name FROM movies WHERE movie_title = 'Tokyo Eyes'"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "Tokyo Eyes' is movie_title, director refers to director_name;",
"index": 84,
"question": "Who was the director of the movie \"Tokyo Eyes\"？",
"question_id": "84",
"split": "train"
} | CREATE TABLE lists_users (
user_id integer, -- example: [2385, 15264]
list_id integer, -- example: [192287, 192313]
list_update_date_utc text, -- example: ['2019-11-26', '2020-05-01']
list_creation_date_utc text, -- example: ['2009-12-18', '2010-01-30']
user_trialist integer, -- example: [1, 0]
... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE lists (\n use... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT COUNT(*) FROM movies WHERE movie_release_year = 2007"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "film released in 2007 refers to movie_release_year = 2007; film refers to movie",
"index": 85,
"question": "How many films were released in 2007?",
"question_id": "85",
"split": "train"
} | CREATE TABLE lists (
user_id integer, -- example: [88260493, 45204418]
list_id integer, -- example: [1, 2]
list_title text, -- example: ['Released in 2012', 'Films that made your kid sister cry', 'Headscratchers']
list_movie_number integer, -- example: [5, 3]
list_update_timestamp_utc text, -- examp... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE ratings_users (\... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT movie_title FROM movies WHERE movie_release_year = 2006 ORDER BY movie_popularity DESC LIMIT 1"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "released in 2006 refers to movie_release_year = 2006; most popular refers to Max(movie_popularity); film refers to movie;",
"index": 86,
"question": "Which of the films released in 2006 was the most popular among Mubi users?",
"question_id": "86",
... | CREATE TABLE ratings_users (
user_id integer, -- example: [41579158, 68654088]
user_trialist integer, -- example: [0, 1]
user_subscriber integer, -- example: [0, 1]
user_avatar_image_url text, -- example: ['https://assets.mubicdn.net/images/avatar']
user_cover_image_url text, -- example: ['https://a... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE lists (\n use... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT COUNT(movie_title) FROM movies WHERE director_name = 'Åke Sandgren'"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "Ake Sandgren is the director name; film refers to movie",
"index": 87,
"question": "How many films did Åke Sandgren direct?",
"question_id": "87",
"split": "train"
} | CREATE TABLE lists (
user_id integer, -- example: [88260493, 45204418]
list_id integer, -- example: [1, 2]
list_title text, -- example: ['director', 'Directors', 'DIRECTORS', 'directors', 'Films that made your kid sister cry', 'Headscratchers']
list_movie_number integer, -- example: [5, 3]
list_upda... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE movies (\n mo... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT movie_title FROM movies WHERE director_name = 'Åke Sandgren' ORDER BY movie_popularity DESC LIMIT 1"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "Alex de la Iclesia is the director name; the most popular refers to Max(movie_popularity); films refers to movies;",
"index": 88,
"question": "Which of the films directed by Álex de la Iclesia is the most popular among Mubi users?",
"question_id": ... | CREATE TABLE movies (
movie_id integer, -- example: [1, 2]
movie_title text, -- example: ['The Director', 'Director', 'Popular', 'Users', 'Most', 'Alex']
movie_release_year integer, -- example: [2007, 2006]
movie_url text, -- example: ['http://mubi.com/films/la-antena', 'http://mubi.com/films/elementary... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE lists_users (\n ... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT movie_release_year FROM movies WHERE movie_title = 'Cops'"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "Cops' is movie_title; released refers to movie_release_year;",
"index": 89,
"question": "When was the movie Cops released?",
"question_id": "89",
"split": "train"
} | CREATE TABLE lists_users (
user_id integer, -- example: [2385, 15264]
list_id integer, -- example: [192287, 192313]
list_update_date_utc text, -- example: ['2019-11-26', '2020-05-01']
list_creation_date_utc text, -- example: ['2009-12-18', '2010-01-30']
user_trialist integer, -- example: [1, 0]
... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE lists_users (\n ... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT director_id FROM movies WHERE movie_title = 'It''s Winter'"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "It's Winter' is movie_title;",
"index": 90,
"question": "Please list the id of the director of the movie \"It's Winter\".",
"question_id": "90",
"split": "train"
} | CREATE TABLE lists_users (
user_id integer, -- example: [2385, 15264]
list_id integer, -- example: [192287, 192313]
list_update_date_utc text, -- example: ['2019-11-26', '2020-05-01']
list_creation_date_utc text, -- example: ['2009-12-18', '2010-01-30']
user_trialist integer, -- example: [1, 0]
... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE lists (\n use... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT user_id FROM lists ORDER BY list_followers DESC LIMIT 1"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "most followers refers to Max(list_followers);",
"index": 91,
"question": "Please provide the ID of the user with the most followers on the list.",
"question_id": "91",
"split": "train"
} | CREATE TABLE lists (
user_id integer, -- example: [88260493, 45204418]
list_id integer, -- example: [1, 2]
list_title text, -- example: ['the most', 'The most', 'please', 'Max', 'please,', 'please!']
list_movie_number integer, -- example: [5, 3]
list_update_timestamp_utc text, -- example: ['2019-01-... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE lists (\n use... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT list_title FROM lists GROUP BY list_title ORDER BY COUNT(list_comments) DESC LIMIT 1"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "the most comments refers to Max(list_comments);",
"index": 92,
"question": "Please provide the title of the list with the most comments on the list.",
"question_id": "92",
"split": "train"
} | CREATE TABLE lists (
user_id integer, -- example: [88260493, 45204418]
list_id integer, -- example: [1, 2]
list_title text, -- example: ['the most', 'The most', 'please', 'Title', 'title', 'Max']
list_movie_number integer, -- example: [5, 3]
list_update_timestamp_utc text, -- example: ['2019-01-24 1... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE ratings_users (\... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT COUNT(T1.user_id) FROM lists_users AS T1 INNER JOIN lists AS T2 ON T1.list_id = T2.list_id WHERE T2.list_followers > 100 AND T1.list_creation_date_utc LIKE '2009%'"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "more than 100 followers refers to list_followers >100; list created by the user in 2009 refers to list_creation_date_utc = '2009';",
"index": 95,
"question": "How many users have more than 100 followers in the list created by users in 2009?",
"que... | CREATE TABLE ratings_users (
user_id integer, -- example: [41579158, 68654088]
CONSTRAINT fk_ratings_users_user_id FOREIGN KEY (user_id) REFERENCES lists_users (user_id)
);
CREATE TABLE movies (
movie_id integer, -- example: [1, 2]
director_id text, -- example: ['131', '73']
PRIMARY KEY (movie_id)
... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE lists_users (\n ... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT T1.user_cover_image_url FROM lists_users AS T1 INNER JOIN lists AS T2 ON T1.list_id = T2.list_id WHERE T2.list_title LIKE 'Georgia related films'"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "Play it cool' is list_title; cover image of user refers to user_cover_image_url;",
"index": 97,
"question": "What's the cover image of the user who created the movie list 'Georgia related films'?",
"question_id": "97",
"split": "train"
} | CREATE TABLE lists_users (
user_id integer, -- example: [2385, 15264]
list_id integer, -- example: [192287, 192313]
list_creation_date_utc text, -- example: ['2009-12-18', '2010-01-30']
user_trialist integer, -- example: [1, 0]
user_subscriber integer, -- example: [1, 0]
user_avatar_image_url te... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE movies (\n mo... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT SUM(T2.list_followers) FROM lists_users AS T1 INNER JOIN lists AS T2 ON T1.list_id = T2.list_id WHERE T1.user_avatar_image_url = 'https://assets.mubicdn.net/images/avatars/74983/images-w150.jpg?1523895214'"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "followers refers to list_followers;",
"index": 98,
"question": "How many followers does the list created by the user whose user_avatar_image_url is https://assets.mubicdn.net/images/avatars/74983/images-w150.jpg?1523895214 have?",
"question_id": "9... | CREATE TABLE movies (
movie_id integer, -- example: [1, 2]
movie_title_language text, -- example: ['en']
director_url text, -- example: ['http://mubi.com/cast/esteban-sapir', 'http://mubi.com/cast/oskar-roehler']
PRIMARY KEY (movie_id)
);
CREATE TABLE lists_users (
user_id integer, -- example: [238... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE ratings_users (\... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT T2.list_title, T1.user_avatar_image_url FROM lists_users AS T1 INNER JOIN lists AS T2 ON T1.list_id = T2.list_id WHERE T1.user_id = 85981819 ORDER BY T2.list_creation_timestamp_utc LIMIT 1"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "user 85981819 refers to user_id = 85981819; first list created refers to Min (list_creation_date_utc);",
"index": 104,
"question": "What was the title of the first list created by a user 85981819? And please provide the user_avatar_image_url.",
"q... | CREATE TABLE ratings_users (
user_id integer, -- example: [41579158, 68654088]
user_trialist integer, -- example: [0, 1]
user_avatar_image_url text, -- example: ['https://assets.mubicdn.net/images/avatar']
user_eligible_for_trial integer, -- example: [1, 0]
CONSTRAINT fk_ratings_users_user_id FOREIG... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE lists_users (\n ... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT movie_release_year FROM movies GROUP BY movie_release_year ORDER BY COUNT(movie_id) DESC LIMIT 1"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "year refers to movie_release_year; most release films refers to MAX(COUNT(movie_id))\n\n",
"index": 112,
"question": "Which year had the most released films?",
"question_id": "112",
"split": "train"
} | CREATE TABLE lists_users (
user_id integer, -- example: [2385, 15264]
list_id integer, -- example: [192287, 192313]
list_update_date_utc text, -- example: ['2019-11-26', '2020-05-01']
list_creation_date_utc text, -- example: ['2009-12-18', '2010-01-30']
user_avatar_image_url text, -- example: ['http... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE ratings_users (\... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT director_id FROM movies GROUP BY director_id ORDER BY COUNT(movie_id) DESC LIMIT 1"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "director that made the most movies refers to MAX(COUNT(movie_id))",
"index": 113,
"question": "Who is the director that made the most movies? Give the director's id.",
"question_id": "113",
"split": "train"
} | CREATE TABLE ratings_users (
user_id integer, -- example: [41579158, 68654088]
user_trialist integer, -- example: [0, 1]
user_avatar_image_url text, -- example: ['https://assets.mubicdn.net/images/avatar']
user_eligible_for_trial integer, -- example: [1, 0]
CONSTRAINT fk_ratings_users_user_id FOREIG... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE ratings_users (\... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT COUNT(movie_id) FROM movies WHERE director_id = ( SELECT director_id FROM movies ORDER BY movie_popularity DESC LIMIT 1 )"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "highest movie popularity refers to MAX(movie_popularity)",
"index": 114,
"question": "How many movies did the director of the highest movie popularity make?",
"question_id": "114",
"split": "train"
} | CREATE TABLE ratings_users (
user_id integer, -- example: [41579158, 68654088]
rating_date_utc text, -- example: ['2017-06-10', '2012-10-02']
user_trialist integer, -- example: [0, 1]
user_subscriber integer, -- example: [0, 1]
user_eligible_for_trial integer, -- example: [1, 0]
CONSTRAINT fk_ra... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE lists (\n use... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT user_id FROM lists_users WHERE user_subscriber = 0 ORDER BY list_creation_date_utc LIMIT 1"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "earliest user created a list refers to MIN(list_creation_date_utc); didn't get any followers refers to user_subscriber = 0",
"index": 116,
"question": "Who was the earliest user created a list but didn't get any followers? Give the user ID.",
"ques... | CREATE TABLE lists (
user_id integer, -- example: [88260493, 45204418]
list_id integer, -- example: [1, 2]
list_title text, -- example: ['create', 'ID.', 'Films that made your kid sister cry', 'Headscratchers']
list_movie_number integer, -- example: [5, 3]
list_update_timestamp_utc text, -- example:... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE movies (\n mo... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT SUM(T1.list_followers) FROM lists AS T1 INNER JOIN lists_users AS T2 ON T1.list_id = T2.list_id GROUP BY T1.user_id ORDER BY COUNT(T1.list_id) DESC LIMIT 1"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "number of followers refers to user_subscriber; posted the most lists refers to MAX(COUNT(list_id))",
"index": 117,
"question": "Give the number of followers for the user who posted the most lists.",
"question_id": "117",
"split": "train"
} | CREATE TABLE movies (
movie_id integer, -- example: [1, 2]
PRIMARY KEY (movie_id)
);
CREATE TABLE ratings_users (
user_id integer, -- example: [41579158, 68654088]
CONSTRAINT fk_ratings_users_user_id FOREIGN KEY (user_id) REFERENCES lists_users (user_id)
);
CREATE TABLE lists_users (
user_id integ... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE lists (\n use... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT SUM(T2.list_followers) FROM lists_users AS T1 INNER JOIN lists AS T2 ON T1.list_id = T2.list_id WHERE T2.list_title LIKE 'Non-American Films about World War II'"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "the list \"Non-American Films about World War II\" refers to list_title = 'Non-American Films about World War II'",
"index": 118,
"question": "How many followers did the user who posted the list \"Non-American Films about World War II\" have?",
"qu... | CREATE TABLE lists (
user_id integer, -- example: [88260493, 45204418]
list_id integer, -- example: [1, 2]
list_title text, -- example: ['Non-American Films about World War II', 'American Films', 'american films', 'World War II', 'World war II', 'WORLD WAR II']
list_update_timestamp_utc text, -- example... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE movies (\n mo... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT T1.user_avatar_image_url FROM lists_users AS T1 INNER JOIN lists AS T2 ON T1.list_id = T2.list_id WHERE T2.list_title LIKE 'Vladimir Vladimirovich Nabokov'"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "the list \"Vladimir Vladimirovich Nabokov\" refers to list_title = 'Vladimir Vladimirovich Nabokov'; portrait picture refers to user_avatar_image_url",
"index": 123,
"question": "Show the portrait picture of the user who created the list \"Vladimir V... | CREATE TABLE movies (
movie_id integer, -- example: [1, 2]
movie_title text, -- example: ['The Portrait', 'Portrait', 'A Portrait', 'Portraits', 'Pictures', 'Pictured']
movie_release_year integer, -- example: [2007, 2006]
movie_title_language text, -- example: ['en']
movie_popularity integer, -- exa... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE ratings_users (\... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT T1.user_has_payment_method FROM lists_users AS T1 INNER JOIN lists AS T2 ON T1.list_id = T2.list_id WHERE T2.list_movie_number = ( SELECT MAX(list_movie_number) FROM lists )"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "the list that contained the most number of the movies refers to MAX(list_movie_number); user_has_payment_method = 1 means the user was a paying subscriber when he created the list ; \nuser_has_payment_method = 0 means the user was not a paying subscriber... | CREATE TABLE ratings_users (
user_id integer, -- example: [41579158, 68654088]
user_trialist integer, -- example: [0, 1]
user_subscriber integer, -- example: [0, 1]
user_eligible_for_trial integer, -- example: [1, 0]
user_has_payment_method integer, -- example: [0, 1]
CONSTRAINT fk_ratings_users... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE movies (\n mo... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT COUNT(T1.user_id) FROM lists_users AS T1 INNER JOIN lists AS T2 ON T1.list_id = T2.list_id WHERE T2.list_followers > 3000 AND T1.user_has_payment_method = 1"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "got more than 3000 followers refers to list_followers > 3000; paying subscribers refer to user_has_payment_method = 1",
"index": 132,
"question": "For the lists that got more than 3000 followers, how many did the users who created those lists are pay... | CREATE TABLE movies (
movie_id integer, -- example: [1, 2]
movie_title text, -- example: ['Follower', 'Follow', 'Users', 'Followed', 'La Antena', 'Elementary Particles']
movie_url text, -- example: ['http://mubi.com/films/la-antena', 'http://mubi.com/films/elementary-particl']
movie_title_language text,... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE lists_users (\n ... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT list_title FROM lists WHERE user_id LIKE 4208563"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "user 4208563 refers to user_id = 4208563",
"index": 138,
"question": "Name all the list titles created by user 4208563.",
"question_id": "138",
"split": "train"
} | CREATE TABLE lists_users (
user_id integer, -- example: [2385, 15264]
list_id integer, -- example: [192287, 192313]
list_update_date_utc text, -- example: ['2019-11-26', '2020-05-01']
list_creation_date_utc text, -- example: ['2009-12-18', '2010-01-30']
user_trialist integer, -- example: [1, 0]
... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE movies (\n mo... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT list_title FROM lists WHERE strftime('%Y', list_update_timestamp_utc) = '2016' ORDER BY list_update_timestamp_utc DESC LIMIT 1"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "created in 2016 refers to list_creation_timestamp_utc like '2016%'; updated most recently refers to MAX(list_update_timestamp_utc)",
"index": 139,
"question": "Among the lists created in 2016, which is the list that was updated most recently.",
"qu... | CREATE TABLE movies (
movie_id integer, -- example: [1, 2]
movie_title text, -- example: ['Most', 'Max', 'La Antena', 'Elementary Particles']
movie_release_year integer, -- example: [2007, 2006]
movie_url text, -- example: ['http://mubi.com/films/la-antena', 'http://mubi.com/films/elementary-particl']
... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE ratings_users (\... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT CAST(SUM(CASE WHEN user_subscriber = 1 THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(list_id) FROM lists_users"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "was a subscriber refers to user_subscriber = 1; percentage refers to DIVIDE(COUNT(user_subscriber = 1),COUNT(list_id))",
"index": 140,
"question": "What is the percentage of list created by user who was a subscriber when he created the list?",
"que... | CREATE TABLE ratings_users (
user_id integer, -- example: [41579158, 68654088]
rating_date_utc text, -- example: ['2017-06-10', '2012-10-02']
user_trialist integer, -- example: [0, 1]
user_subscriber integer, -- example: [0, 1]
user_cover_image_url text, -- example: ['https://assets.mubicdn.net/imag... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE ratings (\n m... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT DISTINCT T2.list_id FROM lists_users AS T1 INNER JOIN lists AS T2 ON T1.list_id = T2.list_id WHERE T1.user_subscriber = 1"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "was a subscriber refers to user_subscriber = 1",
"index": 141,
"question": "Name all lists created by a user who was a subcriber when created the list.",
"question_id": "141",
"split": "train"
} | CREATE TABLE ratings (
movie_id integer, -- example: [1066, 1067]
rating_id integer, -- example: [15610495, 10704606]
rating_url text, -- example: ['http://mubi.com/films/pavee-lackeen-the-']
rating_score integer, -- example: [3, 2]
rating_timestamp_utc text, -- example: ['2017-06-10 12:38:33', '201... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE lists_users (\n ... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT DISTINCT T2.list_title FROM lists_users AS T1 INNER JOIN lists AS T2 ON T1.list_id = T2.list_id WHERE T1.user_eligible_for_trial = 1"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "eligible for trial refers to user_eligible_for_trial = 1",
"index": 142,
"question": "Provide list titles created by user who are eligible for trial when he created the list.",
"question_id": "142",
"split": "train"
} | CREATE TABLE lists_users (
user_id integer, -- example: [2385, 15264]
list_id integer, -- example: [192287, 192313]
list_update_date_utc text, -- example: ['2019-11-26', '2020-05-01']
list_creation_date_utc text, -- example: ['2009-12-18', '2010-01-30']
user_avatar_image_url text, -- example: ['http... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE ratings (\n m... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT COUNT(T1.list_id) FROM lists_users AS T1 INNER JOIN lists AS T2 ON T1.list_id = T2.list_id WHERE T2.list_followers >= 1 AND T1.user_subscriber = 1"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "lists with at least one follower refers to list_followers > = 1; was a subscriber refers to user_subscriber = 1",
"index": 143,
"question": "Among the lists with at least one follower, how many were created by user who was subscriber when created the... | CREATE TABLE ratings (
movie_id integer, -- example: [1066, 1067]
rating_id integer, -- example: [15610495, 10704606]
rating_score integer, -- example: [3, 2]
rating_timestamp_utc text, -- example: ['2017-06-10 12:38:33', '2014-08-15 23:42:31']
critic_likes integer, -- example: [0, 1]
critic_com... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE lists (\n use... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT AVG(list_followers) FROM lists WHERE list_movie_number > 200"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "at least 200 movies in the list refers to list_movie_number > 200; average number of followers refers to avg(list_followers)",
"index": 144,
"question": "For all list titles with at least 200 movies in the list, what is their average number of follow... | CREATE TABLE lists (
user_id integer, -- example: [88260493, 45204418]
list_id integer, -- example: [1, 2]
list_title text, -- example: ['average', 'Title', 'title', 'number 1', 'Number 2', 'Titles.']
list_movie_number integer, -- example: [5, 3]
list_update_timestamp_utc text, -- example: ['2019-01... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE lists_users (\n ... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT DISTINCT T2.list_title FROM lists_users AS T1 INNER JOIN lists AS T2 ON T1.list_id = T2.list_id WHERE T2.list_movie_number < 50 AND T1.user_subscriber = 1"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "have less than 50 movies in the list refers to list_movie_number <50; was a subscriber refers to user_subscriber = 1",
"index": 145,
"question": "List all the titles created by user who was a subsriber when he created the list and have less than 50 m... | CREATE TABLE lists_users (
user_id integer, -- example: [2385, 15264]
list_id integer, -- example: [192287, 192313]
list_update_date_utc text, -- example: ['2019-11-26', '2020-05-01']
list_creation_date_utc text, -- example: ['2009-12-18', '2010-01-30']
user_trialist integer, -- example: [1, 0]
... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE ratings (\n m... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT list_title , datetime(CURRENT_TIMESTAMP, 'localtime') - datetime(list_update_timestamp_utc) FROM lists ORDER BY list_update_timestamp_utc LIMIT 1"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "not been updated for the longest period of time refers to MIN(list_update_timestamp_utc); how long it has not been updated refers to SUBTRACT(CURRENT_TIMESTAMP, list_update_timestamp_utc)",
"index": 146,
"question": "Which title list has not been upd... | CREATE TABLE ratings (
movie_id integer, -- example: [1066, 1067]
rating_id integer, -- example: [15610495, 10704606]
rating_url text, -- example: ['http://mubi.com/films/pavee-lackeen-the-']
rating_score integer, -- example: [3, 2]
rating_timestamp_utc text, -- example: ['2017-06-10 12:38:33', '201... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE lists (\n use... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT T1.user_id, T1.user_subscriber FROM lists_users AS T1 INNER JOIN lists AS T2 ON T1.list_id = T2.list_id WHERE T2.list_title LIKE 'Sound and Vision'"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "list titled 'Sound and Vision' refers to list_title = 'Sound and Vision'; user_subscriber = 1 means the user was a subscriber when he rated the movie; user_subscriber = 0 means the user was not a subscriber when he rated the movie\n\n\n\n",
"index": 14... | CREATE TABLE lists (
user_id integer, -- example: [88260493, 45204418]
list_id integer, -- example: [1, 2]
list_title text, -- example: ['Sound and Vision', 'create', 'vision', 'Rated', 'SOUND', 'sound']
list_movie_number integer, -- example: [5, 3]
list_creation_timestamp_utc text, -- example: ['20... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE lists (\n use... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT list_title , 365 * (strftime('%Y', 'now') - strftime('%Y', list_creation_timestamp_utc)) + 30 * (strftime('%m', 'now') - strftime('%m', list_creation_timestamp_utc)) + strftime('%d', 'now') - strftime('%d', list_creation_timestamp_utc) FROM lists W... | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "more than 200 followers refers to list_followers >200; how long the list has been created refers to SUBTRACT(CURRENT_TIMESTAMP,list_creation_timestamp_utc)",
"index": 148,
"question": "For the list with more than 200 followers, state the title and ho... | CREATE TABLE lists (
user_id integer, -- example: [88260493, 45204418]
list_id integer, -- example: [1, 2]
list_title text, -- example: ['create', 'Title', 'title', 'Films that made your kid sister cry', 'Headscratchers']
list_movie_number integer, -- example: [5, 3]
list_creation_timestamp_utc text... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE lists_users (\n ... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT COUNT(movie_id) FROM movies WHERE movie_release_year BETWEEN '1970' AND '1980' AND movie_popularity > 11000"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "Between 1970 to 1980 refers to movie_release_year between 1970 and 1980; popularity of more than 11,000 refers movie_popularity >11000",
"index": 151,
"question": "Between 1970 to 1980, how many movies with a popularity of more than 11,000 were relea... | CREATE TABLE lists_users (
user_id integer, -- example: [2385, 15264]
list_id integer, -- example: [192287, 192313]
PRIMARY KEY (user_id, list_id),
CONSTRAINT fk_lists_users_user_id FOREIGN KEY (user_id) REFERENCES lists (user_id),
CONSTRAINT fk_lists_users_list_id FOREIGN KEY (list_id) REFERENCES l... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE movies (\n mo... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT COUNT(movie_id) FROM movies WHERE movie_release_year = 1976 AND director_name LIKE 'Felipe Cazals'"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "directed by Felipe Cazals refers to director_name = 'Felipe Cazals' ; realeased on 1976 refers to movie_release_year = 1976",
"index": 152,
"question": "How many movies directed by Felipe Cazals was realeased on 1976?",
"question_id": "152",
"spl... | CREATE TABLE movies (
movie_id integer, -- example: [1, 2]
movie_title text, -- example: ['La Antena', 'Elementary Particles']
movie_release_year integer, -- example: [2007, 2006]
movie_url text, -- example: ['http://mubi.com/films/la-antena', 'http://mubi.com/films/elementary-particl']
movie_title_... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE ratings_users (\... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT director_url FROM movies WHERE movie_title LIKE 'Red Blooded American Girl'"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "movie titled \"Red Blooded American Girl\" refers to movie_title = 'Red Blooded American Girl'",
"index": 153,
"question": "What is the URL to the movie director page on Mubi of the movie titled \"Red Blooded American Girl\"",
"question_id": "153",... | CREATE TABLE ratings_users (
user_id integer, -- example: [41579158, 68654088]
rating_date_utc text, -- example: ['2017-06-10', '2012-10-02']
user_trialist integer, -- example: [0, 1]
user_avatar_image_url text, -- example: ['https://assets.mubicdn.net/images/avatar']
user_cover_image_url text, -- e... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE ratings_users (\... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT list_title FROM lists WHERE list_update_timestamp_utc = ( SELECT list_update_timestamp_utc FROM lists ORDER BY list_update_timestamp_utc DESC LIMIT 1 )"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "updated most recently refers to MAX(list_update_date_utc)",
"index": 154,
"question": "What is the name of the list that was updated most recently?",
"question_id": "154",
"split": "train"
} | CREATE TABLE ratings_users (
user_id integer, -- example: [41579158, 68654088]
rating_date_utc text, -- example: ['2017-06-10', '2012-10-02']
user_trialist integer, -- example: [0, 1]
user_subscriber integer, -- example: [0, 1]
user_avatar_image_url text, -- example: ['https://assets.mubicdn.net/ima... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE ratings (\n m... | bird | {
"ground_truth": {
"db_id": "movie_platform",
"sql": "SELECT user_id FROM lists WHERE list_comments = 142"
},
"style": "rule"
} | {
"db_id": "movie_platform",
"difficulty": "",
"evidence": "list that has 142 comments refers to list_comments = 142",
"index": 155,
"question": "Who created the list that has 142 comments? Indicate the user id of the user, if there are multiple lists with 142 comments, list the user id of the person who crea... | CREATE TABLE ratings (
movie_id integer, -- example: [1066, 1067]
rating_id integer, -- example: [15610495, 10704606]
critic_likes integer, -- example: [0, 1]
critic_comments integer, -- example: [0, 2]
user_id integer, -- example: [41579158, 85981819]
user_has_payment_method integer, -- example... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE titleauthor (\n ... | bird | {
"ground_truth": {
"db_id": "book_publishing_company",
"sql": "SELECT ord_date, SUM(qty) FROM sales GROUP BY ord_date ORDER BY SUM(qty) DESC LIMIT 1"
},
"style": "rule"
} | {
"db_id": "book_publishing_company",
"difficulty": "",
"evidence": "total quantity refers to qty; most ordered quantity refers to order with the highest quantity where MAX(sum(qty))",
"index": 167,
"question": "Which date has the most ordered quantity? What is the total order quantity on that day?",
"quest... | CREATE TABLE titleauthor (
au_id text, -- author id, example: ['172-32-1176', '213-46-8915']
title_id text, -- example: ['PS3333', 'BU1032']
PRIMARY KEY (au_id, title_id),
CONSTRAINT fk_titleauthor_au_id FOREIGN KEY (au_id) REFERENCES authors (au_id),
CONSTRAINT fk_titleauthor_title_id FOREIGN KEY (... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE pub_info (\n ... | bird | {
"ground_truth": {
"db_id": "book_publishing_company",
"sql": "SELECT T2.title FROM sales AS T1 INNER JOIN titles AS T2 ON T1.title_id = T2.title_id WHERE STRFTIME('%Y', T1.ord_date) = '1992' ORDER BY T1.qty DESC LIMIT 1"
},
"style": "rule"
} | {
"db_id": "book_publishing_company",
"difficulty": "",
"evidence": "total quantity refers to qty; most ordered quantity refers to order with the highest quantity where MAX(count(qty)); date refers to ord_date; year 1992 refers to YEAR(ord_date) = 1992",
"index": 168,
"question": "What is the title with the m... | CREATE TABLE pub_info (
pub_id text, -- publication id, example: ['0877', '1389']
logo blob, -- example: ['0x4749463839618B002F00B30F00000000800000', '0x474946383961C2001D00B30F00000000800000']
pr_info text, -- publisher's information, example: ['This is sample text data for Binnet & Ha', 'This is sample te... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE sales (\n sto... | bird | {
"ground_truth": {
"db_id": "book_publishing_company",
"sql": "SELECT T2.title, T2.price, T2.pubdate FROM sales AS T1 INNER JOIN titles AS T2 ON T1.title_id = T2.title_id WHERE T1.payterms = 'ON invoice'"
},
"style": "rule"
} | {
"db_id": "book_publishing_company",
"difficulty": "",
"evidence": "publication date refers to pubdate; payment terms refers to payterms; payterms = 'ON invoice'",
"index": 169,
"question": "List the title, price and publication date for all sales with 'ON invoice' payment terms.",
"question_id": "169",
... | CREATE TABLE sales (
stor_id text, -- store id, example: ['6380', '7066']
ord_num text, -- order number, example: ['6871', '722a']
payterms text, -- example: ['ON invoice', 'Net 60', 'Net 30']
title_id text, -- example: ['BU1032', 'PS2091']
PRIMARY KEY (stor_id, ord_num, title_id),
CONSTRAINT fk... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE titles (\n ti... | bird | {
"ground_truth": {
"db_id": "book_publishing_company",
"sql": "SELECT T1.title FROM titles AS T1 INNER JOIN roysched AS T2 ON T1.title_id = T2.title_id WHERE T2.lorange = 0 AND T2.royalty >= 10"
},
"style": "rule"
} | {
"db_id": "book_publishing_company",
"difficulty": "",
"evidence": "at least 10% royalty refers to royalty > = 10; minimum range is synonym for low range which refers to lorange; without minimum range amount refers to lorange <> 0",
"index": 170,
"question": "What is the title that have at least 10% royalty ... | CREATE TABLE titles (
title_id text, -- example: ['BU1032', 'BU1111']
title text, -- example: ["The Busy Executive's Database Guide", 'Cooking with Computers: Surreptitious Ba']
pub_id text, -- publisher id, example: ['1389', '0736']
price real, -- example: [19.99, 11.95]
royalty integer, -- example... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE titleauthor (\n ... | bird | {
"ground_truth": {
"db_id": "book_publishing_company",
"sql": "SELECT T1.title, T2.royalty FROM titles AS T1 INNER JOIN roysched AS T2 ON T1.title_id = T2.title_id WHERE T2.lorange > 10000 AND T2.hirange < 50000 AND T1.title_ID = 'BU2075'"
},
"style": "rule"
} | {
"db_id": "book_publishing_company",
"difficulty": "",
"evidence": "lorange mean low range; hirange mean high range; range refers to between the low and high range; lorange>10000; hirange<12000",
"index": 171,
"question": "State the title and royalty percentage for title ID BU2075 between 10000 to 50000 rang... | CREATE TABLE titleauthor (
au_id text, -- author id, example: ['172-32-1176', '213-46-8915']
title_id text, -- example: ['BU2075', 'PS3333', 'BU1032']
au_ord integer, -- author ordering, example: [1, 2]
royaltyper integer, -- example: [100, 40]
PRIMARY KEY (au_id, title_id),
CONSTRAINT fk_titlea... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE employee (\n ... | bird | {
"ground_truth": {
"db_id": "book_publishing_company",
"sql": "SELECT T1.title, T2.lorange FROM titles AS T1 INNER JOIN roysched AS T2 ON T1.title_id = T2.title_id ORDER BY T2.royalty DESC LIMIT 1"
},
"style": "rule"
} | {
"db_id": "book_publishing_company",
"difficulty": "",
"evidence": "minimum range is synonym for low range which refers to lorange",
"index": 172,
"question": "Among the titles with royalty percentage, which title has the greatest royalty percentage. State it's minimum range to enjoy this royalty percentage.... | CREATE TABLE employee (
emp_id text, -- employee id, example: ['A-C71970F', 'A-R89858F']
fname text, -- first name, example: ['Aria', 'Annette']
minit text, -- example: ['S', 'M', 'R']
lname text, -- last name, example: ['Cruz', 'Roulet']
job_id integer, -- example: [10, 6]
job_lvl integer, -- j... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE discounts (\n ... | bird | {
"ground_truth": {
"db_id": "book_publishing_company",
"sql": "SELECT T1.title, T2.pub_name FROM titles AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id WHERE T2.country = 'USA'"
},
"style": "rule"
} | {
"db_id": "book_publishing_company",
"difficulty": "",
"evidence": "publisher name refers to pub_name;",
"index": 173,
"question": "Provide a list of titles together with its publisher name for all publishers located in the USA.",
"question_id": "173",
"split": "train"
} | CREATE TABLE discounts (
discounttype text, -- example: ['Initial Customer', 'Volume Discount']
stor_id text, -- store id, example: ['8042']
lowqty integer, -- low quantity, example: [100]
discount real, -- example: [10.5, 6.7]
CONSTRAINT fk_discounts_stor_id FOREIGN KEY (stor_id) REFERENCES stores ... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE pub_info (\n ... | bird | {
"ground_truth": {
"db_id": "book_publishing_company",
"sql": "SELECT MAX(T1.ytd_sales) FROM titles AS T1 INNER JOIN roysched AS T2 ON T1.title_id = T2.title_id WHERE T2.lorange > 20000 AND T2.hirange < 20000"
},
"style": "rule"
} | {
"db_id": "book_publishing_company",
"difficulty": "",
"evidence": "most year to date sales refers to MAX(ytd_sales); range limit means high range which refers to hirange; the 20000 range refers to hirange<20000",
"index": 174,
"question": "State the royalty percentage for the most year to date sale title wi... | CREATE TABLE pub_info (
pub_id text, -- publication id, example: ['0877', '1389']
logo blob, -- example: ['0x4749463839618B002F00B30F00000000800000', '0x474946383961C2001D00B30F00000000800000']
pr_info text, -- publisher's information, example: ['This is sample text data for Binnet & Ha', 'This is sample te... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE jobs (\n job_... | bird | {
"ground_truth": {
"db_id": "book_publishing_company",
"sql": "SELECT T1.title, T1.notes, T2.pub_name FROM titles AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id WHERE STRFTIME('%Y', T1.pubdate) = '1991'"
},
"style": "rule"
} | {
"db_id": "book_publishing_company",
"difficulty": "",
"evidence": "publisher name refers to pub_name; publication date refers to pubdate; published in year 1991 refers to YEAR(pubdate) = 1991",
"index": 175,
"question": "List all titles published in year 1991. Also provide notes details of the title and the... | CREATE TABLE jobs (
job_id integer, -- example: [1, 2]
PRIMARY KEY (job_id)
);
CREATE TABLE sales (
stor_id text, -- store id, example: ['6380', '7066']
ord_num text, -- order number, example: ['6871', '722a']
ord_date datetime, -- order date, example: ['1994-09-14 00:00:00.0', '1994-09-13 00:00:00... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE pub_info (\n ... | bird | {
"ground_truth": {
"db_id": "book_publishing_company",
"sql": "SELECT T1.title, T2.qty FROM titles AS T1 INNER JOIN sales AS T2 ON T1.title_id = T2.title_id INNER JOIN stores AS T3 ON T2.stor_id = T3.stor_id WHERE T2.qty > 20 AND T3.state = 'CA'"
},
"style": "rule"
} | {
"db_id": "book_publishing_company",
"difficulty": "",
"evidence": "qty is abbreviation for quantity; sales of quantity more than 20 refers to qty>20; store refers to stor_name",
"index": 176,
"question": "List all titles with sales of quantity more than 20 and store located in the CA state.",
"question_id... | CREATE TABLE pub_info (
pub_id text, -- publication id, example: ['0877', '1389']
logo blob, -- example: ['0x4749463839618B002F00B30F00000000800000', '0x474946383961C2001D00B30F00000000800000']
PRIMARY KEY (pub_id),
CONSTRAINT fk_pub_info_pub_id FOREIGN KEY (pub_id) REFERENCES publishers (pub_id)
);
CR... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE authors (\n a... | bird | {
"ground_truth": {
"db_id": "book_publishing_company",
"sql": "SELECT T3.stor_id, T2.title FROM sales AS T1 INNER JOIN titles AS T2 ON T1.title_id = T2.title_id INNER JOIN stores AS T3 ON T3.stor_id = T1.stor_id WHERE T3.stor_id = ( SELECT stor_id FROM sales GROUP BY stor_id ORDER BY SUM(qty) DESC LIMIT 1 ) ... | {
"db_id": "book_publishing_company",
"difficulty": "",
"evidence": "qty is abbreviation for quantity; highest quantity refers to MAX(qty); least quantity refers to MIN(qty)",
"index": 177,
"question": "Name the store with the highest quantity in sales? What is the least quantity title from the store's sale?"... | CREATE TABLE authors (
au_id text, -- author id, example: ['172-32-1176', '213-46-8915']
au_lname text, -- author last name, example: ['White', 'Green']
phone text, -- example: ['408 496-7223', '415 986-7020']
state text, -- example: ['CA', 'KS']
zip text, -- example: ['94025', '94618']
contract... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE sales (\n sto... | bird | {
"ground_truth": {
"db_id": "book_publishing_company",
"sql": "SELECT T1.title, T3.pub_name, T2.lorange, T2.hirange, T2.royalty FROM titles AS T1 INNER JOIN roysched AS T2 ON T1.title_id = T2.title_id INNER JOIN publishers AS T3 ON T1.pub_id = T3.pub_id WHERE T1.title_id = 'BU2075'"
},
"style": "rule"
} | {
"db_id": "book_publishing_company",
"difficulty": "",
"evidence": "name the publisher refers to pub_name",
"index": 178,
"question": "Name the title and publisher for title ID BU 2075. Provide all the royalty percentage for all ranges.",
"question_id": "178",
"split": "train"
} | CREATE TABLE sales (
stor_id text, -- store id, example: ['6380', '7066']
ord_num text, -- order number, example: ['6871', '722a']
title_id text, -- example: ['BU1032', 'PS2091']
PRIMARY KEY (stor_id, ord_num, title_id),
CONSTRAINT fk_sales_stor_id FOREIGN KEY (stor_id) REFERENCES stores (stor_id),
... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE sales (\n sto... | bird | {
"ground_truth": {
"db_id": "book_publishing_company",
"sql": "SELECT T2.stor_name , CAST(SUM(CASE WHEN payterms = 'Net 30' THEN qty ELSE 0 END) AS REAL) * 100 / SUM(qty) FROM sales AS T1 INNER JOIN stores AS T2 ON T1.stor_id = T2.stor_id WHERE T1.stor_id = '7066' GROUP BY T2.stor_name"
},
"style": "rule... | {
"db_id": "book_publishing_company",
"difficulty": "",
"evidence": "store with ID 7066 refers to stor_ID = '7066'; 'Net 60' payment terms refers to payterm = 'Net 60'; qty is abbreviation for quantity; percentage = DIVIDE(payterms = 'Net 60', sum(qty))*100",
"index": 179,
"question": "Name the store with ID ... | CREATE TABLE sales (
stor_id text, -- store id, example: ['6380', '7066']
ord_num text, -- order number, example: ['6871', '722a']
ord_date datetime, -- order date, example: ['1994-09-14 00:00:00.0', '1994-09-13 00:00:00.0']
qty integer, -- quantity, example: [5, 3]
payterms text, -- example: ['Net ... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE employee (\n ... | bird | {
"ground_truth": {
"db_id": "book_publishing_company",
"sql": "SELECT T2.pub_name, AVG(T1.ytd_sales) FROM titles AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id WHERE T1.pub_id = '0877' GROUP BY T2.pub_name"
},
"style": "rule"
} | {
"db_id": "book_publishing_company",
"difficulty": "",
"evidence": "publisher id refers to pub_id; publisher name refers to pub_name; average year to date sales = AVG(ytd_sales)",
"index": 180,
"question": "State the publisher name for publisher ID 877? Calculate its average year to date sales.",
"question... | CREATE TABLE employee (
emp_id text, -- employee id, example: ['A-C71970F', 'A-R89858F']
lname text, -- last name, example: ['Cruz', 'Roulet']
job_id integer, -- example: [10, 6]
job_lvl integer, -- job level, example: [87, 152]
pub_id text, -- publisher id, example: ['1389', '9999']
hire_date d... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE jobs (\n job_... | bird | {
"ground_truth": {
"db_id": "book_publishing_company",
"sql": "SELECT fname, lname FROM employee WHERE STRFTIME('%Y', hire_date) < '1990'"
},
"style": "rule"
} | {
"db_id": "book_publishing_company",
"difficulty": "",
"evidence": "hired before year 1990 refers to YEAR(hire_date)<1990",
"index": 181,
"question": "Name all employees who were hired before year 1990.",
"question_id": "181",
"split": "train"
} | CREATE TABLE jobs (
job_id integer, -- example: [1, 2]
PRIMARY KEY (job_id)
);
CREATE TABLE sales (
stor_id text, -- store id, example: ['6380', '7066']
ord_num text, -- order number, example: ['6871', '722a']
ord_date datetime, -- order date, example: ['1994-09-14 00:00:00.0', '1994-09-13 00:00:00... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE stores (\n st... | bird | {
"ground_truth": {
"db_id": "book_publishing_company",
"sql": "SELECT fname, lname, hire_date FROM employee ORDER BY job_lvl LIMIT 1"
},
"style": "rule"
} | {
"db_id": "book_publishing_company",
"difficulty": "",
"evidence": "lowest job level refers to MIN(job_lvl)",
"index": 182,
"question": "Which employee has the lowest job level. State the first name, last name and when he /she was hired.",
"question_id": "182",
"split": "train"
} | CREATE TABLE stores (
stor_id text, -- store id, example: ['6380', '7066']
stor_name text, -- store name, example: ['Eric the Read Books', "Barnum's"]
stor_address text, -- store address, example: ['788 Catamaugus Ave.', '567 Pasadena Ave.']
city text, -- example: ['Seattle', 'Tustin']
state text, -... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE discounts (\n ... | bird | {
"ground_truth": {
"db_id": "book_publishing_company",
"sql": "SELECT STRFTIME('%Y', hire_date) FROM employee GROUP BY STRFTIME('%Y', hire_date) ORDER BY COUNT(emp_id) DESC LIMIT 1"
},
"style": "rule"
} | {
"db_id": "book_publishing_company",
"difficulty": "",
"evidence": "most hired employees refers to MAX(count(emp_id))",
"index": 183,
"question": "In which year has the most hired employees?",
"question_id": "183",
"split": "train"
} | CREATE TABLE discounts (
stor_id text, -- store id, example: ['8042']
discount real, -- example: [10.5, 6.7]
CONSTRAINT fk_discounts_stor_id FOREIGN KEY (stor_id) REFERENCES stores (stor_id)
);
CREATE TABLE employee (
emp_id text, -- employee id, example: ['A-C71970F', 'A-R89858F']
job_id integer, ... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE titleauthor (\n ... | bird | {
"ground_truth": {
"db_id": "book_publishing_company",
"sql": "SELECT T1.fname, T1.lname FROM employee AS T1 INNER JOIN jobs AS T2 ON T1.job_id = T2.job_id WHERE T1.job_lvl = T2.max_lvl"
},
"style": "rule"
} | {
"db_id": "book_publishing_company",
"difficulty": "",
"evidence": "maximum level in their job designation refers to job_lvl = MAX(max_lvl)",
"index": 184,
"question": "List all employees who are at the maximum level in their job designation.",
"question_id": "184",
"split": "train"
} | CREATE TABLE titleauthor (
au_id text, -- author id, example: ['172-32-1176', '213-46-8915']
title_id text, -- example: ['PS3333', 'BU1032']
royaltyper integer, -- example: [100, 40]
PRIMARY KEY (au_id, title_id),
CONSTRAINT fk_titleauthor_au_id FOREIGN KEY (au_id) REFERENCES authors (au_id),
CO... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE stores (\n st... | bird | {
"ground_truth": {
"db_id": "book_publishing_company",
"sql": "SELECT T1.fname, T1.lname, T1.hire_date FROM employee AS T1 INNER JOIN jobs AS T2 ON T1.job_id = T2.job_id WHERE T2.job_desc = 'Chief Financial Officier'"
},
"style": "rule"
} | {
"db_id": "book_publishing_company",
"difficulty": "",
"evidence": "Chief Financial Offer is a job description which refers to job_desc",
"index": 185,
"question": "Name the Chief Executive Officer and when he/she was hired.",
"question_id": "185",
"split": "train"
} | CREATE TABLE stores (
stor_id text, -- store id, example: ['6380', '7066']
stor_name text, -- store name, example: ['Eric the Read Books', "Barnum's"]
stor_address text, -- store address, example: ['788 Catamaugus Ave.', '567 Pasadena Ave.']
city text, -- example: ['Seattle', 'Tustin']
state text, -... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE stores (\n st... | bird | {
"ground_truth": {
"db_id": "book_publishing_company",
"sql": "SELECT T1.fname, T1.lname, T2.pub_name FROM employee AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id WHERE T2.country != 'USA'"
},
"style": "rule"
} | {
"db_id": "book_publishing_company",
"difficulty": "",
"evidence": "not located at USA refers to country! = 'USA'",
"index": 186,
"question": "Who are the employees working for publisher not located in USA? State the employee's name and publisher name.",
"question_id": "186",
"split": "train"
} | CREATE TABLE stores (
stor_id text, -- store id, example: ['6380', '7066']
stor_name text, -- store name, example: ['Eric the Read Books', "Barnum's"]
stor_address text, -- store address, example: ['788 Catamaugus Ave.', '567 Pasadena Ave.']
city text, -- example: ['Seattle', 'Tustin']
state text, -... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE roysched (\n ... | bird | {
"ground_truth": {
"db_id": "book_publishing_company",
"sql": "SELECT T1.fname, T1.lname, T3.job_desc FROM employee AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id INNER JOIN jobs AS T3 ON T1.job_id = T3.job_id WHERE T2.pub_name = 'GGG&G'"
},
"style": "rule"
} | {
"db_id": "book_publishing_company",
"difficulty": "",
"evidence": "name = fname, lname; job description refers to job_desc; publisher refers pub_name",
"index": 187,
"question": "List all employees working for publisher 'GGG&G'. State their name and job description.",
"question_id": "187",
"split": "tra... | CREATE TABLE roysched (
title_id text, -- example: ['BU1032', 'PC1035']
CONSTRAINT fk_roysched_title_id FOREIGN KEY (title_id) REFERENCES titles (title_id)
);
CREATE TABLE employee (
emp_id text, -- employee id, example: ['A-C71970F', 'A-R89858F']
fname text, -- first name, example: ['Aria', 'Annette']... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE titleauthor (\n ... | bird | {
"ground_truth": {
"db_id": "book_publishing_company",
"sql": "SELECT DISTINCT T2.pub_name, T1.type FROM titles AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id ORDER BY T2.pub_name"
},
"style": "rule"
} | {
"db_id": "book_publishing_company",
"difficulty": "",
"evidence": "publisher name refers to pub_name",
"index": 188,
"question": "For each publisher, state the type of titles they published order by the publisher name.",
"question_id": "188",
"split": "train"
} | CREATE TABLE titleauthor (
au_id text, -- author id, example: ['172-32-1176', '213-46-8915']
title_id text, -- example: ['PS3333', 'BU1032']
PRIMARY KEY (au_id, title_id),
CONSTRAINT fk_titleauthor_au_id FOREIGN KEY (au_id) REFERENCES authors (au_id),
CONSTRAINT fk_titleauthor_title_id FOREIGN KEY (... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE titleauthor (\n ... | bird | {
"ground_truth": {
"db_id": "book_publishing_company",
"sql": "SELECT T2.pub_name FROM titles AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id WHERE STRFTIME('%Y', T1.pubdate) = '1991' GROUP BY T1.pub_id, T2.pub_name ORDER BY COUNT(T1.title_id) DESC LIMIT 1"
},
"style": "rule"
} | {
"db_id": "book_publishing_company",
"difficulty": "",
"evidence": "most title published refers to MAX(count(title_id); published in 1991 refers to YEAR(pubdate) = 1991",
"index": 189,
"question": "Name the publisher which has the most titles published in 1991.",
"question_id": "189",
"split": "train"
} | CREATE TABLE titleauthor (
au_id text, -- author id, example: ['172-32-1176', '213-46-8915']
title_id text, -- example: ['PS3333', 'BU1032']
royaltyper integer, -- example: [100, 40]
PRIMARY KEY (au_id, title_id),
CONSTRAINT fk_titleauthor_au_id FOREIGN KEY (au_id) REFERENCES authors (au_id),
CO... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE sales (\n sto... | bird | {
"ground_truth": {
"db_id": "book_publishing_company",
"sql": "SELECT T1.title FROM titles AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id WHERE T2.pub_name = 'Binnet & Hardley' ORDER BY T1.price DESC LIMIT 1"
},
"style": "rule"
} | {
"db_id": "book_publishing_company",
"difficulty": "",
"evidence": "published by refers to pub_name",
"index": 190,
"question": "Name the title with the highest price published by 'Binnet & Hardley'.",
"question_id": "190",
"split": "train"
} | CREATE TABLE sales (
stor_id text, -- store id, example: ['6380', '7066']
ord_num text, -- order number, example: ['6871', '722a']
ord_date datetime, -- order date, example: ['1994-09-14 00:00:00.0', '1994-09-13 00:00:00.0']
qty integer, -- quantity, example: [5, 3]
payterms text, -- example: ['Net ... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE publishers (\n ... | bird | {
"ground_truth": {
"db_id": "book_publishing_company",
"sql": "SELECT T1.fname, T1.lname, T2.job_desc FROM employee AS T1 INNER JOIN jobs AS T2 ON T1.job_id = T2.job_id WHERE T1.job_lvl > 200"
},
"style": "rule"
} | {
"db_id": "book_publishing_company",
"difficulty": "",
"evidence": "job level greater than 200 refers to job_lvl>200; job description refers to job_desc",
"index": 191,
"question": "Among all employees, who have job level greater than 200. State the employee name and job description.",
"question_id": "191"... | CREATE TABLE publishers (
pub_id text, -- publisher id, example: ['0736', '0877']
city text, -- example: ['Boston', 'Washington']
state text, -- example: ['MA', 'DC']
country text, -- example: ['USA', 'Germany']
PRIMARY KEY (pub_id)
);
CREATE TABLE pub_info (
pub_id text, -- publication id, exa... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE roysched (\n ... | bird | {
"ground_truth": {
"db_id": "book_publishing_company",
"sql": "SELECT T3.au_fname, T3.au_lname FROM titles AS T1 INNER JOIN titleauthor AS T2 ON T1.title_id = T2.title_id INNER JOIN authors AS T3 ON T2.au_id = T3.au_id WHERE T1.type = 'business'"
},
"style": "rule"
} | {
"db_id": "book_publishing_company",
"difficulty": "",
"evidence": "business title refers to title under business where type = 'business'",
"index": 192,
"question": "Name all the authors for all business titles.",
"question_id": "192",
"split": "train"
} | CREATE TABLE roysched (
title_id text, -- example: ['BU1032', 'PC1035']
CONSTRAINT fk_roysched_title_id FOREIGN KEY (title_id) REFERENCES titles (title_id)
);
CREATE TABLE sales (
stor_id text, -- store id, example: ['6380', '7066']
ord_num text, -- order number, example: ['6871', '722a']
qty integ... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE stores (\n st... | bird | {
"ground_truth": {
"db_id": "book_publishing_company",
"sql": "SELECT T1.title_id, T1.ytd_sales FROM titles AS T1 INNER JOIN titleauthor AS T2 ON T1.title_id = T2.title_id INNER JOIN authors AS T3 ON T2.au_id = T3.au_id WHERE T3.contract = 0"
},
"style": "rule"
} | {
"db_id": "book_publishing_company",
"difficulty": "",
"evidence": "year to date sales refers to ytd_sales; not on contract refers to contract = 0",
"index": 193,
"question": "List all the titles and year to date sales by author who are not on contract.",
"question_id": "193",
"split": "train"
} | CREATE TABLE stores (
stor_id text, -- store id, example: ['6380', '7066']
PRIMARY KEY (stor_id)
);
CREATE TABLE roysched (
title_id text, -- example: ['BU1032', 'PC1035']
CONSTRAINT fk_roysched_title_id FOREIGN KEY (title_id) REFERENCES titles (title_id)
);
CREATE TABLE pub_info (
pub_id text, --... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE titleauthor (\n ... | bird | {
"ground_truth": {
"db_id": "book_publishing_company",
"sql": "SELECT T1.title FROM titles AS T1 INNER JOIN titleauthor AS T2 ON T1.title_id = T2.title_id INNER JOIN authors AS T3 ON T2.au_id = T3.au_id WHERE T3.contract = 0 AND T3.state = 'CA' ORDER BY T1.ytd_sales DESC LIMIT 1"
},
"style": "rule"
} | {
"db_id": "book_publishing_company",
"difficulty": "",
"evidence": "year to date sales refers to ytd_sales; on contract refers to contract = 1",
"index": 194,
"question": "For all authors from CA who are not on contract, which title of his/hers has the most year to date sales.",
"question_id": "194",
"sp... | CREATE TABLE titleauthor (
au_id text, -- author id, example: ['172-32-1176', '213-46-8915']
title_id text, -- example: ['PS3333', 'BU1032']
au_ord integer, -- author ordering, example: [1, 2]
royaltyper integer, -- example: [100, 40]
PRIMARY KEY (au_id, title_id),
CONSTRAINT fk_titleauthor_au_i... |
[
{
"content": "Task Overview:\nYou are a data science expert. Below, you are provided with a database schema and a natural language question. Your task is to understand the schema and generate a valid SQL query to answer the question.\n\nDatabase Engine:\nSQLite\n\nDatabase Schema:\nCREATE TABLE authors (\n a... | bird | {
"ground_truth": {
"db_id": "book_publishing_company",
"sql": "SELECT T3.au_fname, T3.au_lname FROM titles AS T1 INNER JOIN titleauthor AS T2 ON T1.title_id = T2.title_id INNER JOIN authors AS T3 ON T2.au_id = T3.au_id WHERE T1.title = 'Sushi, Anyone?'"
},
"style": "rule"
} | {
"db_id": "book_publishing_company",
"difficulty": "",
"evidence": "most year to date sales refers to MAX(ytd_sales); on contract refers to contract = 1; name of author = au_fname, au_lname",
"index": 195,
"question": "Name all the authors for 'Sushi, Anyone?'.",
"question_id": "195",
"split": "train"
} | CREATE TABLE authors (
au_id text, -- author id, example: ['172-32-1176', '213-46-8915']
au_lname text, -- author last name, example: ['White', 'Green']
au_fname text, -- author first name, example: ['Johnson', 'Marjorie']
phone text, -- example: ['408 496-7223', '415 986-7020']
address text, -- exa... |
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