Database: beer_factory
Question: Which brand in 2012 has the lowest star rating and contains cane sugar as well as honey?
Evidence: brand refers to BrandName; in 2012 refers to ReviewDate LIKE '2012%'; lowest star rating refers to MIN(StarRating); contains cane sugar as well as honey refers to CaneSugar = 'TRUE' AND Honey = 'TRUE';
SQL: SELECT DISTINCT T1.BrandName FROM rootbeerbrand AS T1 INNER JOIN rootbeerreview AS T2 ON T1.BrandID = T2.BrandID WHERE T1.CaneSugar = 'TRUE' AND T1.Honey = 'TRUE' AND T2.StarRating = 1 AND T2.ReviewDate LIKE '2012%'

Database: food_inspection
Question: Mention the violation type ID and description of high risk category for STARBUCKS.
Evidence: STARBUCKS is the name of the business; high risk category refers to risk_category = 'High Risk';
SQL: SELECT DISTINCT T1.violation_type_id, T1.description FROM violations AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T2.name = 'STARBUCKS' AND T1.risk_category = 'High Risk'

Database: movie_3
Question: Among the films with a rental duration of 7 days, how many are comedies?
Evidence: rental duration of 7 refers to rental_duration = 7; comedies refers to name = 'Comedy'
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 T1.rental_duration = 7 AND T3.name = 'Comedy'

Database: public_review_platform
Question: Find the location of businesses that has business hours from 9 am to 9 pm every Saturday.
Evidence: 9 am refers to opening_time = '9AM'; 9 pm refers to closing_time = '9PM'; every Saturday refers to day_of_week = 'Saturday'; location refers to city
SQL: SELECT T1.city FROM Business AS T1 INNER JOIN Business_Hours AS T2 ON T1.business_id = T2.business_id INNER JOIN Days AS T3 ON T2.day_id = T3.day_id WHERE T2.closing_time LIKE '9PM' AND T2.opening_time LIKE '9AM' AND T3.day_of_week LIKE 'Saturday' GROUP BY T1.city

Database: public_review_platform
Question: List at least 5 active business ID that are good for groups and dancing.
Evidence: "Good for Groups" and "Good for Dancing" are attribute_name; active business refers to active = true'
SQL: SELECT T2.business_id FROM Attributes AS T1 INNER JOIN Business_Attributes AS T2 ON T1.attribute_id = T2.attribute_id INNER JOIN Business AS T3 ON T2.business_id = T3.business_id WHERE T2.attribute_value LIKE 'TRUE' AND T1.attribute_name LIKE 'Good for Dancing' AND T1.attribute_name LIKE 'Good for Groups' LIMIT 5

Database: video_games
Question: How many platforms are available for the game Pro Evolution Soccer 2016?
Evidence: game Pro Evolution Soccer 2016 refers to game_name = 'Pro Evolution Soccer 2016'
SQL: SELECT COUNT(T2.id) FROM game_platform AS T1 INNER JOIN platform AS T2 ON T1.platform_id = T2.id INNER JOIN game_publisher AS T3 ON T1.game_publisher_id = T3.id INNER JOIN game AS T4 ON T3.game_id = T4.id WHERE T4.game_name = 'Pro Evolution Soccer 2016'

Database: retail_world
Question: What were the products supplied by the company in Spain?
Evidence: company in Spain refers to Country = 'Spain'; product supplied refers to ProductName
SQL: SELECT T1.ProductName FROM Products AS T1 INNER JOIN Suppliers AS T2 ON T1.SupplierID = T2.SupplierID WHERE T2.Country = 'Spain'

Database: airline
Question: Among the flights departing from John F. Kennedy International, how many of them arrived earlier than scheduled?
Evidence: departing from refers to ORIGIN; John F. Kennedy International refers to Description = 'New York, NY: John F. Kennedy International'; arrived earlier than scheduled refers to ARR_DELAY < 0;
SQL: SELECT SUM(CASE WHEN T2.ARR_DELAY < 0 THEN 1 ELSE 0 END) AS count FROM Airports AS T1 INNER JOIN Airlines AS T2 ON T1.Code = T2.ORIGIN WHERE T1.Description = 'New York, NY: John F. Kennedy International'

Database: books
Question: How many books were written by author A.J. Ayer?
Evidence: "A.J. Ayer" is the author_name;
SQL: SELECT COUNT(*) FROM book_author AS T1 INNER JOIN author AS T2 ON T1.author_id = T2.author_id WHERE T2.author_name = 'A.J. Ayer'

Database: retail_world
Question: Indicate the courtesy title of the 3 employees who have the lowest salary.
Evidence: courtesy title refers to TitleOfCourtesy; the lowest salary refers to MIN(Salary);
SQL: SELECT TitleOfCourtesy FROM Employees ORDER BY Salary LIMIT 3

Database: movie_platform
Question: For the lists that got more than 3000 followers, how many did the users who created those lists are paying subscribers?
Evidence: got more than 3000 followers refers to list_followers > 3000; paying subscribers refer to user_has_payment_method = 1
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

Database: cs_semester
Question: Describe the students' full names and grades in Intro to BlockChain course.
Evidence: student's full names = f_name, l_name;
SQL: SELECT T1.f_name, T1.l_name, T2.grade FROM student AS T1 INNER JOIN registration AS T2 ON T1.student_id = T2.student_id INNER JOIN course AS T3 ON T2.course_id = T3.course_id WHERE T3.name = 'Intro to BlockChain'

Database: public_review_platform
Question: Calculate the percentage of medium tip length in the list. List out the time when users of medium tip length join Yelp.
Evidence: medium tip length refers to tip_length = 'Medium'; percentage = divide(count(tips where tip_length = 'Medium'), count(tips))*100%; the time when users join Yelp refers to user_yelping_since_year
SQL: SELECT CAST(SUM(CASE WHEN T1.tip_length = 'Medium' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.tip_length), T2.user_yelping_since_year FROM Tips AS T1 INNER JOIN Users AS T2 ON T1.user_id = T2.user_id

Database: synthea
Question: List down the full name of Irish patients diagnosed with the prevalent diseases that have an occurrence greater than the 96% of the average occurrences of all conditions.
Evidence: full name = first, last; Irish refers to ethnicity = 'irish'; prevalent diseases that have an occurrence greater than the 96% of the average occurrences of all conditions = OCCURRENCES > (AVG(MULTIPLY(all_prevalences.OCCURRENCES, 0.96)));
SQL: SELECT DISTINCT T2.first, T2.last FROM conditions AS T1 INNER JOIN patients AS T2 ON T1.PATIENT = T2.patient INNER JOIN all_prevalences AS T3 ON T1.DESCRIPTION = T3.ITEM WHERE T2.ethnicity = 'irish' AND 100 * CAST(T3.OCCURRENCES AS REAL) / ( SELECT AVG(OCCURRENCES) FROM all_prevalences ) > 96

Database: legislator
Question: Which legislators are woman?
Evidence: woman refers to gender_bio = 'F';
SQL: SELECT first_name, last_name FROM historical WHERE gender_bio = 'F'

Database: restaurant
Question: How many Indian restaurants are there in the Los Angeles area?
Evidence: Indian restaurant refers to food_type = 'indian'; the Los Angeles area refers to region = 'los angeles area'
SQL: SELECT COUNT(T1.city) FROM geographic AS T1 INNER JOIN generalinfo AS T2 ON T1.city = T2.city WHERE T2.food_type = 'indian' AND T1.region = 'los angeles area'

Database: public_review_platform
Question: Provide the list of user ID along with review star of which has the review length of medium with business ID of 35.
Evidence: ;
SQL: SELECT user_id, review_stars FROM Reviews WHERE business_id = 15 AND review_length = 'Medium'

Database: video_games
Question: What is the number of sales in region ID 2 with game platform ID 9615?
Evidence: number of sales refers to multiply(num_sales, 100000)
SQL: SELECT T.num_sales * 100000 FROM region_sales AS T WHERE T.region_id = 2 AND T.game_platform_id = 9615