1sf/bird-sql-train-with-schema huggingface dataset:
Database: movies_4
Tables: country, department, gender, genre, keyword, language, language_role, movie, movie_genres, movie_languages, person, movie_crew, production_company, production_country, movie_cast, movie_keywords, movie_company
Columns (table index, column name): -1, *, 0, country_id, 0, country_iso_code, 0, country_name, 1, department_id, 1, department_name, 2, gender_id, 2, gender, 3, genre_id, 3, genre_name, 4, keyword_id, 4, keyword_name, 5, language_id, 5, language_code, 5, language_name, 6, role_id, 6, language_role, 7, movie_id, 7, title, 7, budget, 7, homepage, 7, overview, 7, popularity, 7, release_date, 7, revenue, 7, runtime, 7, movie_status, 7, tagline, 7, vote_average, 7, vote_count, 8, movie_id, 8, genre_id, 9, movie_id, 9, language_id, 9, language_role_id, 10, person_id, 10, person_name, 11, movie_id, 11, person_id, 11, department_id, 11, job, 12, company_id, 12, company_name, 13, movie_id, 13, country_id, 14, movie_id, 14, person_id, 14, character_name, 14, gender_id, 14, cast_order, 15, movie_id, 15, keyword_id, 16, movie_id, 16, company_id
Question: How many movies were produced by "Eddie Murphy Productions"?
Evidence: produced by "Eddie Murphy Productions" refers to company_name = 'Eddie Murphy Productions'
SQL: SELECT COUNT(T1.movie_id) FROM movie_company AS T1 INNER JOIN production_company AS T2 ON T1.company_id = T2.company_id WHERE T2.company_name = 'Eddie Murphy Productions'
Database: movies_4
Tables: country, department, gender, genre, keyword, language, language_role, movie, movie_genres, movie_languages, person, movie_crew, production_company, production_country, movie_cast, movie_keywords, movie_company
Columns (table index, column name): -1, *, 0, country_id, 0, country_iso_code, 0, country_name, 1, department_id, 1, department_name, 2, gender_id, 2, gender, 3, genre_id, 3, genre_name, 4, keyword_id, 4, keyword_name, 5, language_id, 5, language_code, 5, language_name, 6, role_id, 6, language_role, 7, movie_id, 7, title, 7, budget, 7, homepage, 7, overview, 7, popularity, 7, release_date, 7, revenue, 7, runtime, 7, movie_status, 7, tagline, 7, vote_average, 7, vote_count, 8, movie_id, 8, genre_id, 9, movie_id, 9, language_id, 9, language_role_id, 10, person_id, 10, person_name, 11, movie_id, 11, person_id, 11, department_id, 11, job, 12, company_id, 12, company_name, 13, movie_id, 13, country_id, 14, movie_id, 14, person_id, 14, character_name, 14, gender_id, 14, cast_order, 15, movie_id, 15, keyword_id, 16, movie_id, 16, company_id
Question: List all the actors who have played characters with "captain" in their names.
Evidence: List all the actors refers to person_name; characters with "captain" in their names refers to character_name LIKE '%captain%';
SQL: SELECT DISTINCT T1.person_name FROM person AS T1 INNER JOIN movie_cast AS T2 ON T1.person_id = T2.person_id WHERE T2.character_name LIKE '%captain%'
Database: movies_4
Tables: country, department, gender, genre, keyword, language, language_role, movie, movie_genres, movie_languages, person, movie_crew, production_company, production_country, movie_cast, movie_keywords, movie_company
Columns (table index, column name): -1, *, 0, country_id, 0, country_iso_code, 0, country_name, 1, department_id, 1, department_name, 2, gender_id, 2, gender, 3, genre_id, 3, genre_name, 4, keyword_id, 4, keyword_name, 5, language_id, 5, language_code, 5, language_name, 6, role_id, 6, language_role, 7, movie_id, 7, title, 7, budget, 7, homepage, 7, overview, 7, popularity, 7, release_date, 7, revenue, 7, runtime, 7, movie_status, 7, tagline, 7, vote_average, 7, vote_count, 8, movie_id, 8, genre_id, 9, movie_id, 9, language_id, 9, language_role_id, 10, person_id, 10, person_name, 11, movie_id, 11, person_id, 11, department_id, 11, job, 12, company_id, 12, company_name, 13, movie_id, 13, country_id, 14, movie_id, 14, person_id, 14, character_name, 14, gender_id, 14, cast_order, 15, movie_id, 15, keyword_id, 16, movie_id, 16, company_id
Question: What is the most common keyword among all the movies released in 2006?
Evidence: most common keyword refers to max(count(keyword_name)); movies released in 2006 refers to release_date LIKE '%2006%'
SQL: SELECT T3.keyword_name FROM movie AS T1 INNER JOIN movie_keywords AS T2 ON T1.movie_id = T2.movie_id INNER JOIN keyword AS T3 ON T2.keyword_id = T3.keyword_id WHERE T1.release_date LIKE '2006%' GROUP BY T3.keyword_name ORDER BY COUNT(T3.keyword_name) DESC LIMIT 1
Database: movies_4
Tables: country, department, gender, genre, keyword, language, language_role, movie, movie_genres, movie_languages, person, movie_crew, production_company, production_country, movie_cast, movie_keywords, movie_company
Columns (table index, column name): -1, *, 0, country_id, 0, country_iso_code, 0, country_name, 1, department_id, 1, department_name, 2, gender_id, 2, gender, 3, genre_id, 3, genre_name, 4, keyword_id, 4, keyword_name, 5, language_id, 5, language_code, 5, language_name, 6, role_id, 6, language_role, 7, movie_id, 7, title, 7, budget, 7, homepage, 7, overview, 7, popularity, 7, release_date, 7, revenue, 7, runtime, 7, movie_status, 7, tagline, 7, vote_average, 7, vote_count, 8, movie_id, 8, genre_id, 9, movie_id, 9, language_id, 9, language_role_id, 10, person_id, 10, person_name, 11, movie_id, 11, person_id, 11, department_id, 11, job, 12, company_id, 12, company_name, 13, movie_id, 13, country_id, 14, movie_id, 14, person_id, 14, character_name, 14, gender_id, 14, cast_order, 15, movie_id, 15, keyword_id, 16, movie_id, 16, company_id
Question: How many movies have "vi" as their language code?
Evidence: "vi" as their language code refers to language_code = 'vi'
SQL: SELECT COUNT(T1.movie_id) FROM movie_languages AS T1 INNER JOIN language AS T2 ON T1.language_id = T2.language_id WHERE T2.language_code = 'vi'
Database: movies_4
Tables: country, department, gender, genre, keyword, language, language_role, movie, movie_genres, movie_languages, person, movie_crew, production_company, production_country, movie_cast, movie_keywords, movie_company
Columns (table index, column name): -1, *, 0, country_id, 0, country_iso_code, 0, country_name, 1, department_id, 1, department_name, 2, gender_id, 2, gender, 3, genre_id, 3, genre_name, 4, keyword_id, 4, keyword_name, 5, language_id, 5, language_code, 5, language_name, 6, role_id, 6, language_role, 7, movie_id, 7, title, 7, budget, 7, homepage, 7, overview, 7, popularity, 7, release_date, 7, revenue, 7, runtime, 7, movie_status, 7, tagline, 7, vote_average, 7, vote_count, 8, movie_id, 8, genre_id, 9, movie_id, 9, language_id, 9, language_role_id, 10, person_id, 10, person_name, 11, movie_id, 11, person_id, 11, department_id, 11, job, 12, company_id, 12, company_name, 13, movie_id, 13, country_id, 14, movie_id, 14, person_id, 14, character_name, 14, gender_id, 14, cast_order, 15, movie_id, 15, keyword_id, 16, movie_id, 16, company_id
Question: What is the third least common genre?
Evidence: least common genre refers to min(count(genre_name))
SQL: SELECT T2.genre_name FROM movie_genres AS T1 INNER JOIN genre AS T2 ON T1.genre_id = T2.genre_id GROUP BY T2.genre_id ORDER BY COUNT(T1.movie_id) LIMIT 2, 1
Database: movies_4
Tables: country, department, gender, genre, keyword, language, language_role, movie, movie_genres, movie_languages, person, movie_crew, production_company, production_country, movie_cast, movie_keywords, movie_company
Columns (table index, column name): -1, *, 0, country_id, 0, country_iso_code, 0, country_name, 1, department_id, 1, department_name, 2, gender_id, 2, gender, 3, genre_id, 3, genre_name, 4, keyword_id, 4, keyword_name, 5, language_id, 5, language_code, 5, language_name, 6, role_id, 6, language_role, 7, movie_id, 7, title, 7, budget, 7, homepage, 7, overview, 7, popularity, 7, release_date, 7, revenue, 7, runtime, 7, movie_status, 7, tagline, 7, vote_average, 7, vote_count, 8, movie_id, 8, genre_id, 9, movie_id, 9, language_id, 9, language_role_id, 10, person_id, 10, person_name, 11, movie_id, 11, person_id, 11, department_id, 11, job, 12, company_id, 12, company_name, 13, movie_id, 13, country_id, 14, movie_id, 14, person_id, 14, character_name, 14, gender_id, 14, cast_order, 15, movie_id, 15, keyword_id, 16, movie_id, 16, company_id
Question: What is the original language of the movie with the tagline "An offer you can't refuse."?
Evidence: language refers to language_name; original language refers to language_role = 'Original'
SQL: SELECT T3.language_name FROM movie AS T1 INNER JOIN movie_languages AS T2 ON T1.movie_id = T2.movie_id INNER JOIN language AS T3 ON T2.language_id = T3.language_id INNER JOIN language_role AS T4 ON T2.language_role_id = T4.role_id WHERE T4.language_role = 'Original' AND T1.tagline LIKE 'An offer you can%t refuse.'
Database: movies_4
Tables: country, department, gender, genre, keyword, language, language_role, movie, movie_genres, movie_languages, person, movie_crew, production_company, production_country, movie_cast, movie_keywords, movie_company
Columns (table index, column name): -1, *, 0, country_id, 0, country_iso_code, 0, country_name, 1, department_id, 1, department_name, 2, gender_id, 2, gender, 3, genre_id, 3, genre_name, 4, keyword_id, 4, keyword_name, 5, language_id, 5, language_code, 5, language_name, 6, role_id, 6, language_role, 7, movie_id, 7, title, 7, budget, 7, homepage, 7, overview, 7, popularity, 7, release_date, 7, revenue, 7, runtime, 7, movie_status, 7, tagline, 7, vote_average, 7, vote_count, 8, movie_id, 8, genre_id, 9, movie_id, 9, language_id, 9, language_role_id, 10, person_id, 10, person_name, 11, movie_id, 11, person_id, 11, department_id, 11, job, 12, company_id, 12, company_name, 13, movie_id, 13, country_id, 14, movie_id, 14, person_id, 14, character_name, 14, gender_id, 14, cast_order, 15, movie_id, 15, keyword_id, 16, movie_id, 16, company_id
Question: Provide the average revenue of all the French movies.
Evidence: French movies refers to country_name = 'France'; average revenue = AVG(revenue)
SQL: SELECT AVG(T1.revenue) FROM movie AS T1 INNER JOIN production_COUNTry AS T2 ON T1.movie_id = T2.movie_id INNER JOIN COUNTry AS T3 ON T2.COUNTry_id = T3.COUNTry_id WHERE T3.COUNTry_name = 'France'
Database: movies_4
Tables: country, department, gender, genre, keyword, language, language_role, movie, movie_genres, movie_languages, person, movie_crew, production_company, production_country, movie_cast, movie_keywords, movie_company
Columns (table index, column name): -1, *, 0, country_id, 0, country_iso_code, 0, country_name, 1, department_id, 1, department_name, 2, gender_id, 2, gender, 3, genre_id, 3, genre_name, 4, keyword_id, 4, keyword_name, 5, language_id, 5, language_code, 5, language_name, 6, role_id, 6, language_role, 7, movie_id, 7, title, 7, budget, 7, homepage, 7, overview, 7, popularity, 7, release_date, 7, revenue, 7, runtime, 7, movie_status, 7, tagline, 7, vote_average, 7, vote_count, 8, movie_id, 8, genre_id, 9, movie_id, 9, language_id, 9, language_role_id, 10, person_id, 10, person_name, 11, movie_id, 11, person_id, 11, department_id, 11, job, 12, company_id, 12, company_name, 13, movie_id, 13, country_id, 14, movie_id, 14, person_id, 14, character_name, 14, gender_id, 14, cast_order, 15, movie_id, 15, keyword_id, 16, movie_id, 16, company_id
Question: List all the unspecified gender characters.
Evidence: characters refers to character_name; gender = 'Unspecified'
SQL: SELECT T1.character_name FROM movie_cast AS T1 INNER JOIN gender AS T2 ON T1.gender_id = T2.gender_id WHERE T2.gender = 'Unspecified'
Database: movies_4
Tables: country, department, gender, genre, keyword, language, language_role, movie, movie_genres, movie_languages, person, movie_crew, production_company, production_country, movie_cast, movie_keywords, movie_company
Columns (table index, column name): -1, *, 0, country_id, 0, country_iso_code, 0, country_name, 1, department_id, 1, department_name, 2, gender_id, 2, gender, 3, genre_id, 3, genre_name, 4, keyword_id, 4, keyword_name, 5, language_id, 5, language_code, 5, language_name, 6, role_id, 6, language_role, 7, movie_id, 7, title, 7, budget, 7, homepage, 7, overview, 7, popularity, 7, release_date, 7, revenue, 7, runtime, 7, movie_status, 7, tagline, 7, vote_average, 7, vote_count, 8, movie_id, 8, genre_id, 9, movie_id, 9, language_id, 9, language_role_id, 10, person_id, 10, person_name, 11, movie_id, 11, person_id, 11, department_id, 11, job, 12, company_id, 12, company_name, 13, movie_id, 13, country_id, 14, movie_id, 14, person_id, 14, character_name, 14, gender_id, 14, cast_order, 15, movie_id, 15, keyword_id, 16, movie_id, 16, company_id
Question: What are the top 5 most popular movie directors?
Evidence: directors refers to job = 'Director'; most popular refers to max(popularity)
SQL: SELECT T3.person_name FROM movie AS T1 INNER JOIN movie_crew AS T2 ON T1.movie_id = T2.movie_id INNER JOIN person AS T3 ON T2.person_id = T3.person_id WHERE T2.job = 'Director' ORDER BY T1.popularity DESC LIMIT 5
Database: movies_4
Tables: country, department, gender, genre, keyword, language, language_role, movie, movie_genres, movie_languages, person, movie_crew, production_company, production_country, movie_cast, movie_keywords, movie_company
Columns (table index, column name): -1, *, 0, country_id, 0, country_iso_code, 0, country_name, 1, department_id, 1, department_name, 2, gender_id, 2, gender, 3, genre_id, 3, genre_name, 4, keyword_id, 4, keyword_name, 5, language_id, 5, language_code, 5, language_name, 6, role_id, 6, language_role, 7, movie_id, 7, title, 7, budget, 7, homepage, 7, overview, 7, popularity, 7, release_date, 7, revenue, 7, runtime, 7, movie_status, 7, tagline, 7, vote_average, 7, vote_count, 8, movie_id, 8, genre_id, 9, movie_id, 9, language_id, 9, language_role_id, 10, person_id, 10, person_name, 11, movie_id, 11, person_id, 11, department_id, 11, job, 12, company_id, 12, company_name, 13, movie_id, 13, country_id, 14, movie_id, 14, person_id, 14, character_name, 14, gender_id, 14, cast_order, 15, movie_id, 15, keyword_id, 16, movie_id, 16, company_id
Question: List the film with the highest budget in each genre.
Evidence: highest budget refers to max(budget); each genre refers to genre_name; film also means movie; list the film refers to title of movie
SQL: SELECT T3.genre_name, MAX(T1.budget) FROM movie AS T1 INNER JOIN movie_genres AS T2 ON T1.movie_id = T2.movie_id INNER JOIN genre AS T3 ON T2.genre_id = T3.genre_id GROUP BY T3.genre_name
Database: movies_4
Tables: country, department, gender, genre, keyword, language, language_role, movie, movie_genres, movie_languages, person, movie_crew, production_company, production_country, movie_cast, movie_keywords, movie_company
Columns (table index, column name): -1, *, 0, country_id, 0, country_iso_code, 0, country_name, 1, department_id, 1, department_name, 2, gender_id, 2, gender, 3, genre_id, 3, genre_name, 4, keyword_id, 4, keyword_name, 5, language_id, 5, language_code, 5, language_name, 6, role_id, 6, language_role, 7, movie_id, 7, title, 7, budget, 7, homepage, 7, overview, 7, popularity, 7, release_date, 7, revenue, 7, runtime, 7, movie_status, 7, tagline, 7, vote_average, 7, vote_count, 8, movie_id, 8, genre_id, 9, movie_id, 9, language_id, 9, language_role_id, 10, person_id, 10, person_name, 11, movie_id, 11, person_id, 11, department_id, 11, job, 12, company_id, 12, company_name, 13, movie_id, 13, country_id, 14, movie_id, 14, person_id, 14, character_name, 14, gender_id, 14, cast_order, 15, movie_id, 15, keyword_id, 16, movie_id, 16, company_id
Question: What is the title of the movie with the most keywords?
Evidence: most keywords refers to max(count(keyword_id))
SQL: SELECT T1.title FROM movie AS T1 INNER JOIN movie_keywords AS T2 ON T1.movie_id = T2.movie_id GROUP BY T1.title ORDER BY COUNT(T2.keyword_id) DESC LIMIT 1
Database: movies_4
Tables: country, department, gender, genre, keyword, language, language_role, movie, movie_genres, movie_languages, person, movie_crew, production_company, production_country, movie_cast, movie_keywords, movie_company
Columns (table index, column name): -1, *, 0, country_id, 0, country_iso_code, 0, country_name, 1, department_id, 1, department_name, 2, gender_id, 2, gender, 3, genre_id, 3, genre_name, 4, keyword_id, 4, keyword_name, 5, language_id, 5, language_code, 5, language_name, 6, role_id, 6, language_role, 7, movie_id, 7, title, 7, budget, 7, homepage, 7, overview, 7, popularity, 7, release_date, 7, revenue, 7, runtime, 7, movie_status, 7, tagline, 7, vote_average, 7, vote_count, 8, movie_id, 8, genre_id, 9, movie_id, 9, language_id, 9, language_role_id, 10, person_id, 10, person_name, 11, movie_id, 11, person_id, 11, department_id, 11, job, 12, company_id, 12, company_name, 13, movie_id, 13, country_id, 14, movie_id, 14, person_id, 14, character_name, 14, gender_id, 14, cast_order, 15, movie_id, 15, keyword_id, 16, movie_id, 16, company_id
Question: Which department has the most people?
Evidence: department refers to department_name; most people refers to max(count(department_id))
SQL: SELECT T1.department_name FROM department AS T1 INNER JOIN movie_crew AS T2 ON T1.department_id = T2.department_id GROUP BY T1.department_id ORDER BY COUNT(T2.department_id) DESC LIMIT 1
Database: movies_4
Tables: country, department, gender, genre, keyword, language, language_role, movie, movie_genres, movie_languages, person, movie_crew, production_company, production_country, movie_cast, movie_keywords, movie_company
Columns (table index, column name): -1, *, 0, country_id, 0, country_iso_code, 0, country_name, 1, department_id, 1, department_name, 2, gender_id, 2, gender, 3, genre_id, 3, genre_name, 4, keyword_id, 4, keyword_name, 5, language_id, 5, language_code, 5, language_name, 6, role_id, 6, language_role, 7, movie_id, 7, title, 7, budget, 7, homepage, 7, overview, 7, popularity, 7, release_date, 7, revenue, 7, runtime, 7, movie_status, 7, tagline, 7, vote_average, 7, vote_count, 8, movie_id, 8, genre_id, 9, movie_id, 9, language_id, 9, language_role_id, 10, person_id, 10, person_name, 11, movie_id, 11, person_id, 11, department_id, 11, job, 12, company_id, 12, company_name, 13, movie_id, 13, country_id, 14, movie_id, 14, person_id, 14, character_name, 14, gender_id, 14, cast_order, 15, movie_id, 15, keyword_id, 16, movie_id, 16, company_id
Question: What percentage of films are made in the US?
Evidence: films' and 'movies' are synonyms; made in the US refers to country_iso_code = 'US'; percentage = divide(sum(country_id) when country_iso_code = 'US', count(country_id)) * 100 as percentage
SQL: SELECT CAST(COUNT(CASE WHEN T3.COUNTry_iso_code = 'US' THEN T1.movie_id ELSE NULL END) AS REAL) * 100 / COUNT(T1.movie_id) FROM movie AS T1 INNER JOIN production_COUNTry AS T2 ON T1.movie_id = T2.movie_id INNER JOIN COUNTry AS T3 ON T2.COUNTry_id = T3.COUNTry_id
Database: movies_4
Tables: country, department, gender, genre, keyword, language, language_role, movie, movie_genres, movie_languages, person, movie_crew, production_company, production_country, movie_cast, movie_keywords, movie_company
Columns (table index, column name): -1, *, 0, country_id, 0, country_iso_code, 0, country_name, 1, department_id, 1, department_name, 2, gender_id, 2, gender, 3, genre_id, 3, genre_name, 4, keyword_id, 4, keyword_name, 5, language_id, 5, language_code, 5, language_name, 6, role_id, 6, language_role, 7, movie_id, 7, title, 7, budget, 7, homepage, 7, overview, 7, popularity, 7, release_date, 7, revenue, 7, runtime, 7, movie_status, 7, tagline, 7, vote_average, 7, vote_count, 8, movie_id, 8, genre_id, 9, movie_id, 9, language_id, 9, language_role_id, 10, person_id, 10, person_name, 11, movie_id, 11, person_id, 11, department_id, 11, job, 12, company_id, 12, company_name, 13, movie_id, 13, country_id, 14, movie_id, 14, person_id, 14, character_name, 14, gender_id, 14, cast_order, 15, movie_id, 15, keyword_id, 16, movie_id, 16, company_id
Question: What is the average ratio between female and male actors in a movie?
Evidence: female refers to gender = 'Female'；male refers to gender = 'Male'; average ratio = divide(divide(sum(gender_id) when gender = 'Female', sum(gender_id) when gender = 'Male'), count(movie_id)) as percentage
SQL: SELECT CAST(COUNT(CASE WHEN T2.gender = 'Female' THEN T1.person_id ELSE NULL END) AS REAL) / COUNT(CASE WHEN T2.gender = 'Male' THEN T1.person_id ELSE NULL END) FROM movie_cast AS T1 INNER JOIN gender AS T2 ON T1.gender_id = T2.gender_id
Database: movies_4
Tables: country, department, gender, genre, keyword, language, language_role, movie, movie_genres, movie_languages, person, movie_crew, production_company, production_country, movie_cast, movie_keywords, movie_company
Columns (table index, column name): -1, *, 0, country_id, 0, country_iso_code, 0, country_name, 1, department_id, 1, department_name, 2, gender_id, 2, gender, 3, genre_id, 3, genre_name, 4, keyword_id, 4, keyword_name, 5, language_id, 5, language_code, 5, language_name, 6, role_id, 6, language_role, 7, movie_id, 7, title, 7, budget, 7, homepage, 7, overview, 7, popularity, 7, release_date, 7, revenue, 7, runtime, 7, movie_status, 7, tagline, 7, vote_average, 7, vote_count, 8, movie_id, 8, genre_id, 9, movie_id, 9, language_id, 9, language_role_id, 10, person_id, 10, person_name, 11, movie_id, 11, person_id, 11, department_id, 11, job, 12, company_id, 12, company_name, 13, movie_id, 13, country_id, 14, movie_id, 14, person_id, 14, character_name, 14, gender_id, 14, cast_order, 15, movie_id, 15, keyword_id, 16, movie_id, 16, company_id
Question: List the movies released in 1945.
Evidence: List the movies refers to title; released in 1945 refers to release_date LIKE '1945%'
SQL: SELECT title FROM movie WHERE CAST(STRFTIME('%Y', release_date) AS INT) = 1945
Database: movies_4
Tables: country, department, gender, genre, keyword, language, language_role, movie, movie_genres, movie_languages, person, movie_crew, production_company, production_country, movie_cast, movie_keywords, movie_company
Columns (table index, column name): -1, *, 0, country_id, 0, country_iso_code, 0, country_name, 1, department_id, 1, department_name, 2, gender_id, 2, gender, 3, genre_id, 3, genre_name, 4, keyword_id, 4, keyword_name, 5, language_id, 5, language_code, 5, language_name, 6, role_id, 6, language_role, 7, movie_id, 7, title, 7, budget, 7, homepage, 7, overview, 7, popularity, 7, release_date, 7, revenue, 7, runtime, 7, movie_status, 7, tagline, 7, vote_average, 7, vote_count, 8, movie_id, 8, genre_id, 9, movie_id, 9, language_id, 9, language_role_id, 10, person_id, 10, person_name, 11, movie_id, 11, person_id, 11, department_id, 11, job, 12, company_id, 12, company_name, 13, movie_id, 13, country_id, 14, movie_id, 14, person_id, 14, character_name, 14, gender_id, 14, cast_order, 15, movie_id, 15, keyword_id, 16, movie_id, 16, company_id
Question: Provide the ID and ISO code of Belgium.
Evidence: ID refers to country_id; ISO code refers to country_iso_code; Belgium refers to country_name = 'Belgium'
SQL: SELECT COUNTry_id, COUNTry_iso_code FROM COUNTry WHERE COUNTry_name = 'Belgium'
Database: movies_4
Tables: country, department, gender, genre, keyword, language, language_role, movie, movie_genres, movie_languages, person, movie_crew, production_company, production_country, movie_cast, movie_keywords, movie_company
Columns (table index, column name): -1, *, 0, country_id, 0, country_iso_code, 0, country_name, 1, department_id, 1, department_name, 2, gender_id, 2, gender, 3, genre_id, 3, genre_name, 4, keyword_id, 4, keyword_name, 5, language_id, 5, language_code, 5, language_name, 6, role_id, 6, language_role, 7, movie_id, 7, title, 7, budget, 7, homepage, 7, overview, 7, popularity, 7, release_date, 7, revenue, 7, runtime, 7, movie_status, 7, tagline, 7, vote_average, 7, vote_count, 8, movie_id, 8, genre_id, 9, movie_id, 9, language_id, 9, language_role_id, 10, person_id, 10, person_name, 11, movie_id, 11, person_id, 11, department_id, 11, job, 12, company_id, 12, company_name, 13, movie_id, 13, country_id, 14, movie_id, 14, person_id, 14, character_name, 14, gender_id, 14, cast_order, 15, movie_id, 15, keyword_id, 16, movie_id, 16, company_id
Question: List the character names played by Catherine Deneuve.
SQL: SELECT T2.character_name FROM person AS T1 INNER JOIN movie_cast AS T2 ON T1.person_id = T2.person_id WHERE T1.person_name = 'Catherine Deneuve'