You are SQL Expert thats help analysing the question to generate correct SQL query. Given a database schema, a question. Use the examples to break down the question to phrases and generate correct what to select, the SQL conditions to use for each pharase, then determine which tables to use. A condition must have left hand side and right hand side, for example "A = B", "A in [1,2]". This is not a condition ```movie_popularity```, do not generate condition like this example. Please follow the format in the examples. database schema : table pages , columns = [ pages.words ( integer | values : 1081 , 68 ) , pages.page ( integer | values : 1 , 2 ) , pages.pid ( integer | primary key | comment : page id | values : 1 , 2 ) , pages.title ( text | values : Àbac , Abadia ) , pages.lid ( integer | comment : language id | values : 1 ) , pages.revision ( integer | values : 28236978 , 24086480 ) ] table words , columns = [ words.word ( text | values : +,2 , +,33 ) , words.wid ( integer | primary key | comment : word id | values : 2148990 , 2506463 ) , words.occurrences ( integer | values : 242 , 16841 ) ] table langs , columns = [ langs.pages ( integer | values : 1129144 ) , langs.words ( integer | values : 2764996 ) , langs.lid ( integer | primary key | comment : language id | values : 1 ) , langs.lang ( text | comment : language | values : ca ) , langs.locale ( text | values : ca_ES ) ] table pages_words , columns = [ pages_words.pid ( integer | primary key | comment : page id | values : 1 , 2 ) , pages_words.wid ( integer | primary key | comment : word id | values : 1 , 2 ) , pages_words.occurrences ( integer | values : 30 , 8 ) ] table langs_words , columns = [ langs_words.wid ( integer | primary key | comment : word id | values : 1 , 2 ) , langs_words.occurrences ( integer | values : 242 , 16841 ) , langs_words.lid ( integer | primary key | comment : language id | values : 1 ) ] table biwords , columns = [ biwords.occurrences ( integer | values : 4 , 3 ) , biwords.lid ( integer | primary key | comment : language id | values : 1 ) , biwords.w1st ( integer | primary key | comment : word id of the first word | values : 1 , 2 ) , biwords.w2nd ( integer | primary key | comment : word id of the second word | values : 2 , 4 ) ] foreign keys : pages.lid = langs.lid langs_words.wid = words.wid langs_words.lid = langs.lid pages_words.wid = words.wid pages_words.pid = pages.pid biwords.w2nd = words.wid biwords.w1st = words.wid biwords.lid = langs.lid Matched contents are written in this format table.column (some values can be found in that column) matched contents : pages.words ( 1500 ) pages.page ( 1500 ) pages.pid ( 1500 ) pages.title ( Pages , 1500 ) words.word ( pages , words , calculates , differents , divides , percentages , counts , page's , wordes ) pages_words.occurrences ( 1500 ) langs_words.wid ( 1500 ) langs_words.occurrences ( 1500 ) biwords.occurrences ( 1500 ) biwords.w1st ( 1500 ) biwords.w2nd ( 1500 ) Question: Calculate the percentage of pages that have 1500 different words. External knowledge: DIVIDE(COUNT(pages WHERE words = 1500), COUNT(pages)) as percentage; Answer in this format: Goal to select: - The question asks for ['the percentage of pages']. + 'the percentage of pages': From the External knowledge `DIVIDE(COUNT(pages WHERE words = 1500), COUNT(pages)) as percentage`, so `the percentage of pages` refers to `COUNT(CASE WHEN pages.words = 1500 THEN 1 ELSE NULL END) * 100.0 / COUNT(pages.pid)`. - The query should select: [`COUNT(CASE WHEN pages.words = 1500 THEN 1 ELSE NULL END) * 100.0 / COUNT(pages.pid)`] Condition: - 'pages that have 1500 different words': refers to column `pages.words`, so the condition is ```pages.words = 1500```. Tables to use: - From the goal to select and condition, the query should use tables [`pages`]. Final SQL query: ``` SELECT COUNT(CASE WHEN pages.words = 1500 THEN 1 ELSE NULL END) * 100.0 / COUNT(pages.pid) FROM pages; ``` ========= database schema : table lists , columns = [ lists.list_followers ( integer | values : 5 , 1 ) , lists.list_update_timestamp_utc ( text | values : 2019-01-24 19:16:18 , 2018-12-03 15:12:20 ) , lists.list_url ( text ) , lists.list_id ( integer | primary key | values : 1 , 2 ) , lists.list_creation_timestamp_utc ( text | values : 2009-11-11 00:02:21 , 2009-11-11 00:05:11 ) , lists.list_title ( text | values : Headscratchers ) , lists.user_id ( integer | values : 88260493 , 45204418 ) , lists.list_description ( text ) , lists.list_movie_number ( integer | values : 5 , 3 ) , lists.list_comments ( integer | values : 3 , 2 ) ] table lists_users , columns = [ lists_users.list_id ( integer | primary key | values : 192287 , 192313 ) , lists_users.list_update_date_utc ( text | values : 2019-11-26 , 2020-05-01 ) , lists_users.user_id ( integer | primary key | values : 2385 , 15264 ) , lists_users.list_creation_date_utc ( text | values : 2009-12-18 , 2010-01-30 ) , lists_users.user_subscriber ( integer | values : 1 , 0 ) , lists_users.user_trialist ( integer | values : 1 , 0 ) , lists_users.user_has_payment_method ( text | values : 1 , 0 ) , lists_users.user_eligible_for_trial ( text | values : 0 , 1 ) , lists_users.user_avatar_image_url ( text ) , lists_users.user_cover_image_url ( text ) ] table movies , columns = [ movies.director_name ( text | values : Esteban Sapir , Oskar Roehler ) , movies.movie_title ( text | values : La Antena , Elementary Particles ) , movies.director_id ( text | values : 131 , 73 ) , movies.movie_url ( text ) , movies.movie_id ( integer | primary key | values : 1 , 2 ) , movies.director_url ( text ) , movies.movie_popularity ( integer | values : 105 , 23 ) , movies.movie_image_url ( text ) , movies.movie_release_year ( integer | values : 2007 , 2006 ) , movies.movie_title_language ( text | values : en ) ] table ratings_users , columns = [ ratings_users.user_id ( integer | values : 41579158 , 68654088 ) , ratings_users.rating_date_utc ( text | values : 2017-06-10 , 2012-10-02 ) , ratings_users.user_subscriber ( integer | values : 0 , 1 ) , ratings_users.user_trialist ( integer | values : 0 , 1 ) , ratings_users.user_eligible_for_trial ( integer | values : 1 , 0 ) , ratings_users.user_has_payment_method ( integer | values : 0 , 1 ) , ratings_users.user_cover_image_url ( text ) , ratings_users.user_avatar_image_url ( text ) ] table ratings , columns = [ ratings.critic ( text ) , ratings.rating_timestamp_utc ( text | values : 2017-06-10 12:38:33 , 2014-08-15 23:42:31 ) , ratings.user_id ( integer | values : 41579158 , 85981819 ) , ratings.rating_id ( integer | values : 15610495 , 10704606 ) , ratings.rating_score ( integer | values : 3 , 2 ) , ratings.critic_comments ( integer | values : 0 , 2 ) , ratings.movie_id ( integer | values : 1066 , 1067 ) , ratings.critic_likes ( integer | values : 0 , 1 ) , ratings.rating_url ( text ) , ratings.user_subscriber ( integer | values : 0 , 1 ) ] foreign keys : lists.user_id = lists_users.user_id ratings_users.user_id = lists_users.user_id lists_users.user_id = lists.user_id lists_users.list_id = lists.list_id ratings.user_id = ratings_users.user_id ratings.rating_id = ratings.rating_id ratings.user_id = lists_users.user_id ratings.movie_id = movies.movie_id Matched contents are written in this format table.column (some values can be found in that column) matched contents : lists.list_id ( 2012 ) lists.list_title ( on MUBI , on Mubi , Mubi , MUBI , The List. ) Question: What are the URL to the list page on Mubi of the lists with followers between 1-2 and whose last update timestamp was on 2012? External knowledge: 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'; Answer in this format: Goal to select: - The question asks for ['the URL to the list page on Mubi']. + 'the URL to the list page on Mubi', from the External knowledge, 'URL to the list page on Mubi refers to list_url', so 'the URL to the list page on Mubi' refers to `lists.list_url`. - The query should select: [`lists.list_url`] Condition: - 'with followers between 1-2': check with the external knowledge `list_followers = 1 OR list_followers = 2`, so `with followers between 1-2` refers to column `lists.list_followers`, the condition is `lists.list_followers BETWEEN 1 AND 2`. - 'last update timestamp was on 2012': check with the external knowledge `list_update_timestamp_utc BETWEEN '2012-1-1' AND '2012-12-31'` refers to column `lists.list_update_timestamp_utc`. The condition is `lists.list_update_timestamp_utc BETWEEN '2012-01-01' AND '2012-12-31'`. Tables to use: - From the goal to select and condition, the query should use tables [`lists`]. Final SQL query: ``` SELECT lists.list_url FROM lists WHERE lists.list_followers BETWEEN 1 AND 2 AND lists.list_update_timestamp_utc BETWEEN '2012-01-01' AND '2012-12-31'; ``` ========= database schema : table matchs , columns = [ matchs.div ( text | comment : division | values : B1 , D1 ) , matchs.ftr ( text | comment : final-time results | values : A , D ) , matchs.hometeam ( text | values : Club Brugge , Antwerp ) , matchs.season ( integer | values : 2021 , 2020 ) , matchs.awayteam ( text | values : Charleroi , Mouscron ) , matchs.date ( date | values : 2020-08-08 , 2020-08-09 ) , matchs.fthg ( integer | comment : final-time home-team goals | values : 0 , 1 ) , matchs.ftag ( integer | comment : final-time away-team goals | values : 1 , 0 ) ] table divisions , columns = [ divisions.division ( text | primary key | values : B1 , D1 ) , divisions.country ( text | values : Belgium , Deutschland ) , divisions.name ( text | values : Division 1A , Bundesliga ) ] foreign keys : matchs.div = divisions.division Matched contents are written in this format table.column (some values can be found in that column) matched contents : matchs.season ( 2017 ) divisions.country ( Spain ) divisions.name ( LaLiga ) Question: From the Spanish LaLiga division in the 2017 season, which team won the most times as a local team and by what percentage? External knowledge: local team refers to hometeam; Spanish means belong to the country = 'Spain'; LaLiga is a name of division; won as a local team refers to ftr = 'H', where H stands for home victory; divIDE(COUNT(div where name = 'LaLiga', country = 'Spain', season = 2017, FRT = 'H'), COUNT(div where name = 'LaLiga', country = 'Spain', season = 2017)) as percentage; Answer in this format: Goal to select: - The question asks for ['which team won the most times as a local team', 'by what percentage']. + 'which team won the most times as a local team': From the external knowledge, `local team refers to hometeam`, so this needs to select 'hometeam'. + 'by what percentage': From the external knowledge `divIDE(COUNT(div where name = 'LaLiga', country = 'Spain', season = 2017, FRT = 'H'), COUNT(div where name = 'LaLiga', country = 'Spain', season = 2017))`, so this needs to select `COUNT(CASE WHEN divisions.name = 'LaLiga' AND divisions.country = 'Spain' AND matchs.season = 2017 AND matchs.ftr = 'H' THEN 1 ELSE NULL END) * 100.0 / COUNT(CASE WHEN divisions.name = 'LaLiga' AND divisions.country = 'Spain' AND matchs.season = 2017 THEN 1 ELSE NULL END)`. - The query should select: [`hometeam`, `COUNT(CASE WHEN divisions.name = 'LaLiga' AND divisions.country = 'Spain' AND matchs.season = 2017 AND matchs.ftr = 'H' THEN 1 ELSE NULL END) * 100.0 / COUNT(CASE WHEN divisions.name = 'LaLiga' AND divisions.country = 'Spain' AND matchs.season = 2017 THEN 1 ELSE NULL END)`]. - 'won the most times': The query also needs to order the result by percentage and get top-1 result. Condition: - 'From the Spanish': From external knowledge, `Spanish means belong to the country = 'Spain'`, this refers to the column `divisions.country`, so the condition is `divisions.country = 'Spain'`. - 'LaLiga division': From external knowledge `LaLiga is a name of division`, this refers to column 'divisions.name', so the condition is `divisions.name = 'LaLiga'`. - '2017 season': From external knowledge `season = 2017`, this refers to column 'matchs.season', so the condition `matchs.season = 2017`. - 'won as a local team': From external knowledge `won as a local team refers to ftr = 'H'`, so this refers to column 'matchs.ftr', so the condition is `matchs.ftr = 'H'`. Tables to use: - From the goal to select and condition, the query should use tables [`matchs`, `divisions`]. Final SQL query: ``` SELECT matchs.hometeam, COUNT(CASE WHEN divisions.name = 'LaLiga' AND divisions.country = 'Spain' AND matchs.season = 2017 AND matchs.ftr = 'H' THEN 1 ELSE NULL END) * 100.0 / COUNT(CASE WHEN divisions.name = 'LaLiga' AND divisions.country = 'Spain' AND matchs.season = 2017 THEN 1 ELSE NULL END) AS percentage FROM matchs JOIN divisions ON matchs.div = divisions.division WHERE divisions.country = 'Spain' AND divisions.name = 'LaLiga' AND matchs.season = 2017 ORDER BY percentage DESC LIMIT 1; ``` ========= database schema : table movies , columns = [ movies.movie_release_year ( integer | values : 2007 , 2006 ) , movies.movie_title ( text | values : La Antena , Elementary Particles ) , movies.movie_popularity ( integer | values : 105 , 23 ) , movies.movie_id ( integer | primary key | values : 1 , 2 ) , movies.movie_title_language ( text | values : en ) , movies.director_name ( text | values : Esteban Sapir , Oskar Roehler ) , movies.movie_url ( text ) , movies.movie_image_url ( text ) , movies.director_id ( text | values : 131 , 73 ) , movies.director_url ( text ) ] table ratings_users , columns = [ ratings_users.user_id ( integer | values : 41579158 , 68654088 ) , ratings_users.user_subscriber ( integer | values : 0 , 1 ) , ratings_users.user_trialist ( integer | values : 0 , 1 ) , ratings_users.user_has_payment_method ( integer | values : 0 , 1 ) , ratings_users.rating_date_utc ( text | values : 2017-06-10 , 2012-10-02 ) , ratings_users.user_cover_image_url ( text ) , ratings_users.user_eligible_for_trial ( integer | values : 1 , 0 ) , ratings_users.user_avatar_image_url ( text ) ] table lists_users , columns = [ lists_users.list_id ( integer | primary key | values : 192287 , 192313 ) , lists_users.user_id ( integer | primary key | values : 2385 , 15264 ) , lists_users.user_trialist ( integer | values : 1 , 0 ) , lists_users.user_has_payment_method ( text | values : 1 , 0 ) , lists_users.user_subscriber ( integer | values : 1 , 0 ) , lists_users.user_eligible_for_trial ( text | values : 0 , 1 ) , lists_users.user_cover_image_url ( text ) , lists_users.user_avatar_image_url ( text ) , lists_users.list_creation_date_utc ( text | values : 2009-12-18 , 2010-01-30 ) , lists_users.list_update_date_utc ( text | values : 2019-11-26 , 2020-05-01 ) ] table lists , columns = [ lists.list_title ( text | values : Headscratchers ) , lists.list_movie_number ( integer | values : 5 , 3 ) , lists.list_id ( integer | primary key | values : 1 , 2 ) , lists.user_id ( integer | values : 88260493 , 45204418 ) , lists.list_description ( text ) , lists.list_comments ( integer | values : 3 , 2 ) , lists.list_url ( text ) , lists.list_followers ( integer | values : 5 , 1 ) , lists.list_third_image_url ( text ) , lists.list_second_image_url ( text ) ] table ratings , columns = [ ratings.movie_id ( integer | values : 1066 , 1067 ) , ratings.rating_id ( integer | values : 15610495 , 10704606 ) , ratings.critic ( text ) , ratings.user_id ( integer | values : 41579158 , 85981819 ) , ratings.rating_score ( integer | values : 3 , 2 ) , ratings.critic_comments ( integer | values : 0 , 2 ) , ratings.critic_likes ( integer | values : 0 , 1 ) , ratings.rating_url ( text ) , ratings.user_trialist ( integer | values : 0 , 1 ) , ratings.user_subscriber ( integer | values : 0 , 1 ) ] foreign keys : lists.user_id = lists_users.user_id ratings_users.user_id = lists_users.user_id lists_users.user_id = lists.user_id lists_users.list_id = lists.list_id ratings.user_id = ratings_users.user_id ratings.rating_id = ratings.rating_id ratings.user_id = lists_users.user_id ratings.movie_id = movies.movie_id Matched contents are written in this format table.column (some values can be found in that column) matched contents : movies.movie_release_year ( 1945 ) movies.movie_title ( Year , 1945 , Order , The Years , Release ) movies.movie_id ( 1945 ) lists_users.list_id ( 1945 ) lists.list_title ( 1945 , Sort , Titles. , title , Title ) lists.list_id ( 1945 ) ratings.movie_id ( 1945 ) ratings.rating_id ( 1945 ) Question: Sort the listing by the descending order of movie popularity. External knowledge: released in the year 1945 refers to movie_release_year = 1945; Name movie titles released in year 1945. Answer in this format: Goal to select: - The question asks for ['movie titles', 'sorted by popularity in descending order']. + 'movie titles': this refers to `movies.movie_title`. - The query should select: [`movies.movie_title`] - The query needs to `sort by the descending order of movie popularity`, this refers to `ORDER BY movies.movie_popularity DESC`. Condition: - 'released in the year 1945': from external knowledge `released in the year 1945`, so this refers to column `movies.movie_release_year`, so the condition is `movies.movie_release_year = 1945`. Tables to use: - From the goal to select and condition, the query should use tables [`movies`]. Final SQL query: ``` SELECT movies.movie_title FROM movies WHERE movies.movie_release_year = 1945 ORDER BY movies.movie_popularity DESC; ```