Database: ice_hockey_draft
Question: What is the percentage of players who were born in Denmark and weight above 154 lbs?
Evidence: percentage = MULTIPLY(DIVIDE(SUM(weight_in_lbs > 154 and nation = 'Denmark'), COUNT(ELITEID)), 100); players refers to PlayerName; born in Denmark refers to nation = 'Denmark'; weight above 154 lbs refers to weight_in_lbs > 154;
SQL: SELECT CAST(COUNT(CASE WHEN T1.nation = 'Denmark' AND T2.weight_in_lbs > 154 THEN T1.ELITEID ELSE NULL END) AS REAL) * 100 / COUNT(T1.ELITEID) FROM PlayerInfo AS T1 INNER JOIN weight_info AS T2 ON T1.weight = T2.weight_id

Database: movie_3
Question: How many non-active clients have not returned the rented material?
Evidence: non-active clients refers to active = 0; not returning a rented material refers to rental_date is null
SQL: SELECT COUNT(T2.customer_id) FROM rental AS T1 INNER JOIN customer AS T2 ON T1.customer_id = T2.customer_id WHERE T2.active = 0

Database: sales_in_weather
Question: Give the station pressure status recorded by the weather station which contained no.12 store on 2012/5/15.
Evidence: no.12 store refers to store_nbr = 12; on 2012/5/15 refers to date = '2012-05-15'; station pressure status refers to stnpressure
SQL: SELECT T1.stnpressure FROM weather AS T1 INNER JOIN relation AS T2 ON T1.station_nbr = T2.station_nbr WHERE T1.`date` = '2012-05-15' AND T2.store_nbr = 12

Database: movie_3
Question: Among the films rented by Natalie Meyer, describe the titles and categories of the films which were rented in February 2006.
Evidence: category refers to name; rented in February 2006 refers to year(rental_date) = 2006 and month (rental_rate) = 2
SQL: SELECT T3.title, T2.name FROM film_category AS T1 INNER JOIN category AS T2 ON T1.category_id = T2.category_id INNER JOIN film AS T3 ON T1.film_id = T3.film_id INNER JOIN inventory AS T4 ON T3.film_id = T4.film_id INNER JOIN customer AS T5 ON T4.store_id = T5.store_id INNER JOIN rental AS T6 ON T4.inventory_id = T6.inventory_id WHERE T5.first_name = 'Natalie' AND T5.last_name = 'Meyer' AND STRFTIME('%Y',T3.rental_rate) = '2006' AND STRFTIME('%m',T3.rental_rate) = '2'

Database: talkingdata
Question: Between device ID of "-9215352913819630000" and "-9222956879900150000", mention the age and gender of device user who participated more events.
Evidence: more events refers to MAX(COUNT(event_id));
SQL: SELECT T.age, T.gender FROM ( SELECT T2.age, T2.gender, COUNT(T1.device_id) AS num FROM events AS T1 INNER JOIN gender_age AS T2 ON T1.device_id = T2.device_id WHERE T1.device_id BETWEEN -9215352913819630000 AND -9222956879900150000 GROUP BY T2.age, T2.gender ) AS T ORDER BY T.num DESC LIMIT 1

Database: university
Question: Provide the number of staff at the University of Auckland in 2015.
Evidence: University of Auckland refers to university_name = 'University of Auckland'; in 2015 refers to year = 2015; number of staff refers to DIVIDE(num_students, student_staff_ratio)
SQL: SELECT CAST(SUM(T1.num_students) AS REAL) / SUM(T1.student_staff_ratio) FROM university_year AS T1 INNER JOIN university AS T2 ON T1.university_id = T2.id WHERE T2.university_name = 'University of Auckland' AND T1.year = 2015

Database: human_resources
Question: By what percentage is the average salary of Trainees higher than the minimum salary of this postion?
Evidence: AVG(salary); Trainee is a position title; minimum salary refers to minsalary; calculation = DIVIDE(SUBTRACT(AVG(salary), minsalary), minsalary) * 100
SQL: SELECT 100 * (AVG(CAST(REPLACE(SUBSTR(T1.salary, 4), ',', '') AS REAL)) - CAST(REPLACE(SUBSTR(T2.minsalary, 4), ',', '') AS REAL)) / CAST(REPLACE(SUBSTR(T2.minsalary, 4), ',', '') AS REAL) AS per FROM employee AS T1  INNER JOIN position AS T2  ON T1.positionID = T2.positionID WHERE T2.positiontitle = 'Trainee'

Database: public_review_platform
Question: What is the average Elitestar rating for a Yelp_Business that closes at 12PM on Sundays?
Evidence: average Elitestar rating refers to DIVIDE(SUM(stars), COUNT(business_id)); closes at 12PM refers to closing_time = '12PM'; on Sundays refers to day_of_week = 'Sunday'
SQL: SELECT CAST(SUM(T3.stars) AS REAL) / COUNT(T1.business_id) AS "average stars" FROM Business_Hours AS T1 INNER JOIN Days AS T2 ON T1.day_id = T2.day_id INNER JOIN Business AS T3 ON T1.business_id = T3.business_id WHERE T2.day_of_week LIKE 'Sunday' AND T1.closing_time LIKE '12PM'

Database: legislator
Question: Among all the current legislators whose religion is Roman Catholic, what is the percentage of the ones without an instagram account?
Evidence: religion is Roman Catholic refers to religion_bio = 'Roman Catholic'; calculation = MULTIPLY(DIVIDE(COUNT(instagram is null), COUNT(bioguide_id)), 1.0)
SQL: SELECT CAST(SUM(CASE WHEN T1.instagram IS NULL THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(*) FROM `social-media` AS T1 INNER JOIN current AS T2 ON T1.bioguide = T2.bioguide_id WHERE T2.religion_bio = 'Roman Catholic'

Database: public_review_platform
Question: User No. 70271 only has given one tip to the Yelp business, which category was that business belonged to?
Evidence: user No. refers to user_id; short tip refers to tip_length = 'short'; category refers to category_name;
SQL: SELECT T4.category_name FROM Tips AS T1 INNER JOIN Business AS T2 ON T1.business_id = T2.business_id INNER JOIN Business_Categories AS T3 ON T2.business_id = T3.business_id INNER JOIN Categories AS T4 ON T3.category_id = T4.category_id WHERE T1.user_id = 70271

Database: citeseer
Question: Among all the DB class type citation, which word is the most frequently cited?
Evidence: class type refers to class_label; class_label = 'DB'; word that is most frequently cited refers to max(count(word_cited_id);
SQL: SELECT T2.word_cited_id FROM paper AS T1 INNER JOIN content AS T2 ON T1.paper_id = T2.paper_id WHERE T1.class_label = 'DB' GROUP BY T2.word_cited_id ORDER BY COUNT(T2.word_cited_id) DESC LIMIT 1

Database: chicago_crime
Question: What is the email address to contact the administrator of Central Chicago?
Evidence: email address refers to email; Central Chicago refers to district_name = 'Central'
SQL: SELECT email FROM District WHERE district_name = 'Central'

Database: movie_3
Question: How many documentary films are rated PG-13?
Evidence: documentary film refers to category.name = 'documentary'; rated PG-13 refers to rating = 'PG-13'
SQL: SELECT COUNT(T1.film_id) FROM film AS T1 INNER JOIN film_category AS T2 ON T1.film_id = T2.film_id INNER JOIN category AS T3 ON T2.category_id = T3.category_id WHERE T3.name = 'Documentary' AND T1.rating = 'PG-13'

Database: world
Question: Give the head of the state of the country with the lowest percentage use of English as their language.
Evidence: head of the state refers to HeadOfState; lowest percentage use of English as their language refers to MIN(Percentage WHERE `Language` = 'English');
SQL: SELECT T1.HeadOfState FROM Country AS T1 INNER JOIN CountryLanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = 'English' ORDER BY T2.Percentage LIMIT 1

Database: simpson_episodes
Question: List down the title of episode S20-E1, S20-E2 & S20-E3.
Evidence: episode S20-E1, S20-E2 & S20-E3 refers to episode_id = 'S20-E1' and episode_id = 'S20-E2' and episode_id = 'S20-E3'
SQL: SELECT title FROM Episode WHERE episode_id IN ('S20-E1', 'S20-E2', 'S20-E3');

Database: address
Question: How many postal points are there under the congress representative from the House of Representatives in Mississippi?
Evidence: postal points refer to zip_code; Mississippi is the name of the state, in which name = 'Mississippi';
SQL: SELECT COUNT(T2.zip_code) FROM congress AS T1 INNER JOIN zip_congress AS T2 ON T1.cognress_rep_id = T2.district WHERE T1.state = 'Mississippi'