1sf/bird-sql-train-with-schema huggingface dataset:
Database: food_inspection
Tables: businesses, inspections, violations
Columns (table index, column name): -1, *, 0, business_id, 0, name, 0, address, 0, city, 0, postal_code, 0, latitude, 0, longitude, 0, phone_number, 0, tax_code, 0, business_certificate, 0, application_date, 0, owner_name, 0, owner_address, 0, owner_city, 0, owner_state, 0, owner_zip, 1, business_id, 1, score, 1, date, 1, type, 2, business_id, 2, date, 2, violation_type_id, 2, risk_category, 2, description
Question: List owner's name of businesses with a 100 score.
Evidence: owner's name of businesses refers to owner_name;
SQL: SELECT DISTINCT T2.owner_name FROM inspections AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T1.score = 100
Database: food_inspection
Tables: businesses, inspections, violations
Columns (table index, column name): -1, *, 0, business_id, 0, name, 0, address, 0, city, 0, postal_code, 0, latitude, 0, longitude, 0, phone_number, 0, tax_code, 0, business_certificate, 0, application_date, 0, owner_name, 0, owner_address, 0, owner_city, 0, owner_state, 0, owner_zip, 1, business_id, 1, score, 1, date, 1, type, 2, business_id, 2, date, 2, violation_type_id, 2, risk_category, 2, description
Question: Among the businesses within the postal code 94117, what is total number of businesses with a high risk category?
Evidence: businesses with a high risk category refer to business_id where risk_category = 'High Risk';
SQL: SELECT COUNT(DISTINCT T2.business_id) FROM violations AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T2.postal_code = 94117 AND T1.risk_category = 'High Risk'
Database: food_inspection
Tables: businesses, inspections, violations
Columns (table index, column name): -1, *, 0, business_id, 0, name, 0, address, 0, city, 0, postal_code, 0, latitude, 0, longitude, 0, phone_number, 0, tax_code, 0, business_certificate, 0, application_date, 0, owner_name, 0, owner_address, 0, owner_city, 0, owner_state, 0, owner_zip, 1, business_id, 1, score, 1, date, 1, type, 2, business_id, 2, date, 2, violation_type_id, 2, risk_category, 2, description
Question: Among the businesses with score that ranges from 70 to 80, list their violation type ID and risk category.
Evidence: businesses with score that ranges from 70 to 80 refer to business_id where score between 80 and 90;
SQL: SELECT DISTINCT T1.violation_type_id, T1.risk_category FROM violations AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id INNER JOIN inspections AS T3 ON T2.business_id = T3.business_id WHERE T3.score BETWEEN 70 AND 80
Database: food_inspection
Tables: businesses, inspections, violations
Columns (table index, column name): -1, *, 0, business_id, 0, name, 0, address, 0, city, 0, postal_code, 0, latitude, 0, longitude, 0, phone_number, 0, tax_code, 0, business_certificate, 0, application_date, 0, owner_name, 0, owner_address, 0, owner_city, 0, owner_state, 0, owner_zip, 1, business_id, 1, score, 1, date, 1, type, 2, business_id, 2, date, 2, violation_type_id, 2, risk_category, 2, description
Question: List the tax code and inspection type of the business named "Rue Lepic".
Evidence: "Rue Lepic" is the name of the business;
SQL: SELECT DISTINCT T3.tax_code, T2.type FROM violations AS T1 INNER JOIN inspections AS T2 ON T1.business_id = T2.business_id INNER JOIN businesses AS T3 ON T2.business_id = T3.business_id WHERE T3.name = 'Rue Lepic'
Database: food_inspection
Tables: businesses, inspections, violations
Columns (table index, column name): -1, *, 0, business_id, 0, name, 0, address, 0, city, 0, postal_code, 0, latitude, 0, longitude, 0, phone_number, 0, tax_code, 0, business_certificate, 0, application_date, 0, owner_name, 0, owner_address, 0, owner_city, 0, owner_state, 0, owner_zip, 1, business_id, 1, score, 1, date, 1, type, 2, business_id, 2, date, 2, violation_type_id, 2, risk_category, 2, description
Question: In businesses that violates 103157 on May 27, 2016 , what is the name of the business that has an unscheduled inspection?
Evidence: businesses that violates 103157 refer to business_id where violation_type_id = 103157; date = '2016-05-27'; unscheduled inspection refers to type = 'Routine - Unscheduled';
SQL: SELECT DISTINCT T3.name FROM violations AS T1 INNER JOIN inspections AS T2 ON T1.business_id = T2.business_id INNER JOIN businesses AS T3 ON T2.business_id = T3.business_id WHERE T1.`date` = '2016-05-27' AND T1.violation_type_id = 103157 AND T2.type = 'Routine - Unscheduled'
Database: food_inspection
Tables: businesses, inspections, violations
Columns (table index, column name): -1, *, 0, business_id, 0, name, 0, address, 0, city, 0, postal_code, 0, latitude, 0, longitude, 0, phone_number, 0, tax_code, 0, business_certificate, 0, application_date, 0, owner_name, 0, owner_address, 0, owner_city, 0, owner_state, 0, owner_zip, 1, business_id, 1, score, 1, date, 1, type, 2, business_id, 2, date, 2, violation_type_id, 2, risk_category, 2, description
Question: Who is the owner of the business that has a high risk violation of 103109 and described as unclean or unsanitary food contact surfaces?
Evidence: owner refers to owner_name; high risk violation of 103109 and described as unclean or unsanitary food contact surfaces refers to risk_category = 'High Risk' where violation_type_id = 103109 and description = 'Unclean or unsanitary food contact surfaces';
SQL: SELECT DISTINCT T2.owner_name FROM violations AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T1.risk_category = 'High Risk' AND T1.violation_type_id = 103109 AND T1.description = 'Unclean or unsanitary food contact surfaces'
Database: food_inspection
Tables: businesses, inspections, violations
Columns (table index, column name): -1, *, 0, business_id, 0, name, 0, address, 0, city, 0, postal_code, 0, latitude, 0, longitude, 0, phone_number, 0, tax_code, 0, business_certificate, 0, application_date, 0, owner_name, 0, owner_address, 0, owner_city, 0, owner_state, 0, owner_zip, 1, business_id, 1, score, 1, date, 1, type, 2, business_id, 2, date, 2, violation_type_id, 2, risk_category, 2, description
Question: Among the owners from Cameron Park, what is the business name of the business with a score of 100?
Evidence: Cameron Park is a name of city;
SQL: SELECT DISTINCT T2.name FROM inspections AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T2.owner_city = 'Cameron Park' AND T1.score = 100
Database: food_inspection
Tables: businesses, inspections, violations
Columns (table index, column name): -1, *, 0, business_id, 0, name, 0, address, 0, city, 0, postal_code, 0, latitude, 0, longitude, 0, phone_number, 0, tax_code, 0, business_certificate, 0, application_date, 0, owner_name, 0, owner_address, 0, owner_city, 0, owner_state, 0, owner_zip, 1, business_id, 1, score, 1, date, 1, type, 2, business_id, 2, date, 2, violation_type_id, 2, risk_category, 2, description
Question: List the violation type ID of business with business ID from 30 to 50 and located at 747 IRVING St, San Francisco.
Evidence: business ID from 30 to 50 refers to business_id between 30 and 50; address = '747 IRVING St'; city = 'San Francisco';
SQL: SELECT DISTINCT T1.violation_type_id FROM violations AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T2.business_id BETWEEN 30 AND 50 AND T2.address = '747 IRVING St' AND T2.city = 'San Francisco'
Database: food_inspection
Tables: businesses, inspections, violations
Columns (table index, column name): -1, *, 0, business_id, 0, name, 0, address, 0, city, 0, postal_code, 0, latitude, 0, longitude, 0, phone_number, 0, tax_code, 0, business_certificate, 0, application_date, 0, owner_name, 0, owner_address, 0, owner_city, 0, owner_state, 0, owner_zip, 1, business_id, 1, score, 1, date, 1, type, 2, business_id, 2, date, 2, violation_type_id, 2, risk_category, 2, description
Question: What is the owner's name of the of the business that violates 103156 on June 12, 2014?
Evidence: business that violates 103156 on June 12, 2014 refers to business_id where violation_type_id = 103156 and date = '2014-06-12';
SQL: SELECT DISTINCT T2.owner_name FROM violations AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T1.violation_type_id = 103156 AND T1.`date` = '2014-06-12'
Database: food_inspection
Tables: businesses, inspections, violations
Columns (table index, column name): -1, *, 0, business_id, 0, name, 0, address, 0, city, 0, postal_code, 0, latitude, 0, longitude, 0, phone_number, 0, tax_code, 0, business_certificate, 0, application_date, 0, owner_name, 0, owner_address, 0, owner_city, 0, owner_state, 0, owner_zip, 1, business_id, 1, score, 1, date, 1, type, 2, business_id, 2, date, 2, violation_type_id, 2, risk_category, 2, description
Question: In businesses with an owner address 500 California St, 2nd Floor of Silicon Valley, list the type of inspection of the business with the highest score.
Evidence: the highest score MAX(score); Silicon Valley is located in 'SAN FRANCISCO';
SQL: SELECT T1.type FROM inspections AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T2.owner_address = '500 California St, 2nd Floor' AND T2.owner_city = 'SAN FRANCISCO' ORDER BY T1.score DESC LIMIT 1
Database: food_inspection
Tables: businesses, inspections, violations
Columns (table index, column name): -1, *, 0, business_id, 0, name, 0, address, 0, city, 0, postal_code, 0, latitude, 0, longitude, 0, phone_number, 0, tax_code, 0, business_certificate, 0, application_date, 0, owner_name, 0, owner_address, 0, owner_city, 0, owner_state, 0, owner_zip, 1, business_id, 1, score, 1, date, 1, type, 2, business_id, 2, date, 2, violation_type_id, 2, risk_category, 2, description
Question: Among the violations in 2016, how many of them have unscheduled inspections?
Evidence: unscheduled inspections refer to type = 'Routine - Unschedule'; year(date) = 2016;
SQL: SELECT COUNT(T2.business_id) FROM violations AS T1 INNER JOIN inspections AS T2 ON T1.business_id = T2.business_id WHERE STRFTIME('%Y', T1.`date`) = '2016' AND T2.type = 'Routine - Unscheduled'
Database: food_inspection
Tables: businesses, inspections, violations
Columns (table index, column name): -1, *, 0, business_id, 0, name, 0, address, 0, city, 0, postal_code, 0, latitude, 0, longitude, 0, phone_number, 0, tax_code, 0, business_certificate, 0, application_date, 0, owner_name, 0, owner_address, 0, owner_city, 0, owner_state, 0, owner_zip, 1, business_id, 1, score, 1, date, 1, type, 2, business_id, 2, date, 2, violation_type_id, 2, risk_category, 2, description
Question: List the business' name and risk category of businesses with a score greater than the 80% of average score of all businesses.
Evidence: score greater than the 80% of average score of all businesses refers to score > MULTIPLY(0.8, avg(score) from inspections);
SQL: SELECT DISTINCT T1.name, T3.risk_category FROM businesses AS T1 INNER JOIN inspections AS T2 ON T1.business_id = T2.business_id INNER JOIN violations AS T3 ON T1.business_id = T3.business_id WHERE T2.score > 0.8 * ( SELECT AVG(score) FROM inspections )
Database: food_inspection
Tables: businesses, inspections, violations
Columns (table index, column name): -1, *, 0, business_id, 0, name, 0, address, 0, city, 0, postal_code, 0, latitude, 0, longitude, 0, phone_number, 0, tax_code, 0, business_certificate, 0, application_date, 0, owner_name, 0, owner_address, 0, owner_city, 0, owner_state, 0, owner_zip, 1, business_id, 1, score, 1, date, 1, type, 2, business_id, 2, date, 2, violation_type_id, 2, risk_category, 2, description
Question: In businesses with a score lower than 95 and located around the postal code of 94110, what is the percentage of businesses with a risk category of low risk?
Evidence: DIVIDE(COUNT(business_id where risk_category = 'Low Risk', score < 95 and postal_code = 94110), COUNT(business_id where score < 95 and postal_code = 94110)) as percentage;
SQL: SELECT CAST(SUM(CASE WHEN T1.risk_category = 'Low Risk' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.risk_category) FROM violations AS T1 INNER JOIN inspections AS T2 ON T1.business_id = T2.business_id INNER JOIN businesses AS T3 ON T2.business_id = T3.business_id WHERE T2.score < 95 AND T3.postal_code = 94110
Database: craftbeer
Tables: breweries, beers
Columns (table index, column name): -1, *, 0, id, 0, name, 0, city, 0, state, 1, id, 1, brewery_id, 1, abv, 1, ibu, 1, name, 1, style, 1, ounces
Question: Which distinct state makes beer that has the least amount of bitterness?
SQL: SELECT DISTINCT T2.state, T1.ibu FROM beers AS T1 INNER JOIN breweries AS T2 ON T1.brewery_id = T2.id WHERE T1.ibu IS NOT NULL AND T1.ibu = ( SELECT MIN(ibu) FROM beers )
Database: craftbeer
Tables: breweries, beers
Columns (table index, column name): -1, *, 0, id, 0, name, 0, city, 0, state, 1, id, 1, brewery_id, 1, abv, 1, ibu, 1, name, 1, style, 1, ounces
Question: Where in New York can you locate the brewery that makes the bitterest beer? List both the brewery's name and the name of the city.
Evidence: The more IBU, the more bitter the beer is, bitterest means highest IBU.
SQL: SELECT T2.name, T2.city FROM beers AS T1 INNER JOIN breweries AS T2 ON T1.brewery_id = T2.id WHERE T2.state = 'NY' ORDER BY T1.ibu DESC LIMIT 1
Database: craftbeer
Tables: breweries, beers
Columns (table index, column name): -1, *, 0, id, 0, name, 0, city, 0, state, 1, id, 1, brewery_id, 1, abv, 1, ibu, 1, name, 1, style, 1, ounces
Question: What is the average alcohol content per 12-ounce beer bottle produced by Boston Beer Company?
SQL: SELECT AVG(T1.abv) FROM beers AS T1 INNER JOIN breweries AS T2 ON T1.brewery_id = T2.id WHERE T2.name = 'Boston Beer Company' AND T1.ounces = 12
Database: craftbeer
Tables: breweries, beers
Columns (table index, column name): -1, *, 0, id, 0, name, 0, city, 0, state, 1, id, 1, brewery_id, 1, abv, 1, ibu, 1, name, 1, style, 1, ounces
Question: Of all the beer styles produced by Stevens Point Brewery, how many percent do they allot for American Adjunct Lager?
Evidence: Percent allotted = count(American Adjunct Lager beer styles) / count(styles) * 100%
SQL: SELECT CAST(SUM(IIF(T1.style = 'American Adjunct Lager', 1, 0)) AS REAL) * 100 / COUNT(T1.brewery_id) FROM beers AS T1 INNER JOIN breweries AS T2 ON T1.brewery_id = T2.id WHERE T2.name = 'Stevens Point Brewery'
Database: craftbeer
Tables: breweries, beers
Columns (table index, column name): -1, *, 0, id, 0, name, 0, city, 0, state, 1, id, 1, brewery_id, 1, abv, 1, ibu, 1, name, 1, style, 1, ounces
Question: Which city and state produces the most and least bitter beer, and what is the difference in bitterness between the two? List also the names of the beer.
Evidence: The more IBU, the more bitter the beer is, most bitter means highest IBU; The less IBU, the less bitter the beer is, least bitter means lowest IBU
SQL: SELECT T1.state, T1.city, T2.name, T2.ibu FROM breweries AS T1 INNER JOIN beers AS T2 ON T1.id = T2.brewery_id GROUP BY T1.state, T1.city, T2.name, T2.ibu HAVING MAX(ibu) AND MIN(ibu) LIMIT 2
Database: craftbeer
Tables: breweries, beers
Columns (table index, column name): -1, *, 0, id, 0, name, 0, city, 0, state, 1, id, 1, brewery_id, 1, abv, 1, ibu, 1, name, 1, style, 1, ounces
Question: When compared to the total number of breweries in the US producing American Blonde Ale, how many in the state of Wisconsin produces American Blonde Ale? Indicate your answer in percentage (%).
Evidence: Percentage of the state of Wisconsin produces American Blonde Ale could be computed by count(breweries in Wisconsin producing American Blonde Ale) / count(all breweries)
SQL: SELECT CAST(SUM(IIF(T2.state = 'WI', 1, 0)) AS REAL) * 100 / COUNT(T1.id) FROM beers AS T1 INNER JOIN breweries AS T2 ON T1.brewery_id = T2.id WHERE T1.style = 'American Blonde Ale'
Database: cookbook
Tables: Ingredient, Recipe, Nutrition, Quantity
Columns (table index, column name): -1, *, 0, ingredient_id, 0, category, 0, name, 0, plural, 1, recipe_id, 1, title, 1, subtitle, 1, servings, 1, yield_unit, 1, prep_min, 1, cook_min, 1, stnd_min, 1, source, 1, intro, 1, directions, 2, recipe_id, 2, protein, 2, carbo, 2, alcohol, 2, total_fat, 2, sat_fat, 2, cholestrl, 2, sodium, 2, iron, 2, vitamin_c, 2, vitamin_a, 2, fiber, 2, pcnt_cal_carb, 2, pcnt_cal_fat, 2, pcnt_cal_prot, 2, calories, 3, quantity_id, 3, recipe_id, 3, ingredient_id, 3, max_qty, 3, min_qty, 3, unit, 3, preparation, 3, optional
Question: What is the title of the recipe that is most likely to gain weight?
Evidence: most likely to gain weight refers to MAX(total_fat)
SQL: SELECT T1.title FROM Recipe AS T1 INNER JOIN Nutrition AS T2 ON T1.recipe_id = T2.recipe_id ORDER BY T2.total_fat DESC LIMIT 1
Database: cookbook
Tables: Ingredient, Recipe, Nutrition, Quantity
Columns (table index, column name): -1, *, 0, ingredient_id, 0, category, 0, name, 0, plural, 1, recipe_id, 1, title, 1, subtitle, 1, servings, 1, yield_unit, 1, prep_min, 1, cook_min, 1, stnd_min, 1, source, 1, intro, 1, directions, 2, recipe_id, 2, protein, 2, carbo, 2, alcohol, 2, total_fat, 2, sat_fat, 2, cholestrl, 2, sodium, 2, iron, 2, vitamin_c, 2, vitamin_a, 2, fiber, 2, pcnt_cal_carb, 2, pcnt_cal_fat, 2, pcnt_cal_prot, 2, calories, 3, quantity_id, 3, recipe_id, 3, ingredient_id, 3, max_qty, 3, min_qty, 3, unit, 3, preparation, 3, optional
Question: What is the unsaturated fat content in the recipe "Raspberry Chiffon Pie"?
Evidence: Raspberry Chiffon Pie refers to title; unsaturated fat refers to SUBTRACT(total_fat, sat_fat)
SQL: SELECT T2.total_fat - T2.sat_fat FROM Recipe AS T1 INNER JOIN Nutrition AS T2 ON T1.recipe_id = T2.recipe_id WHERE T1.title = 'Raspberry Chiffon Pie'
Database: cookbook
Tables: Ingredient, Recipe, Nutrition, Quantity
Columns (table index, column name): -1, *, 0, ingredient_id, 0, category, 0, name, 0, plural, 1, recipe_id, 1, title, 1, subtitle, 1, servings, 1, yield_unit, 1, prep_min, 1, cook_min, 1, stnd_min, 1, source, 1, intro, 1, directions, 2, recipe_id, 2, protein, 2, carbo, 2, alcohol, 2, total_fat, 2, sat_fat, 2, cholestrl, 2, sodium, 2, iron, 2, vitamin_c, 2, vitamin_a, 2, fiber, 2, pcnt_cal_carb, 2, pcnt_cal_fat, 2, pcnt_cal_prot, 2, calories, 3, quantity_id, 3, recipe_id, 3, ingredient_id, 3, max_qty, 3, min_qty, 3, unit, 3, preparation, 3, optional
Question: Please list the titles of all the recipes that are salt/sodium-free.
Evidence: salt/sodium-free refers to sodium < 5
SQL: SELECT T1.title FROM Recipe AS T1 INNER JOIN Nutrition AS T2 ON T1.recipe_id = T2.recipe_id WHERE T2.sodium < 5
Database: cookbook
Tables: Ingredient, Recipe, Nutrition, Quantity
Columns (table index, column name): -1, *, 0, ingredient_id, 0, category, 0, name, 0, plural, 1, recipe_id, 1, title, 1, subtitle, 1, servings, 1, yield_unit, 1, prep_min, 1, cook_min, 1, stnd_min, 1, source, 1, intro, 1, directions, 2, recipe_id, 2, protein, 2, carbo, 2, alcohol, 2, total_fat, 2, sat_fat, 2, cholestrl, 2, sodium, 2, iron, 2, vitamin_c, 2, vitamin_a, 2, fiber, 2, pcnt_cal_carb, 2, pcnt_cal_fat, 2, pcnt_cal_prot, 2, calories, 3, quantity_id, 3, recipe_id, 3, ingredient_id, 3, max_qty, 3, min_qty, 3, unit, 3, preparation, 3, optional
Question: Please list the titles of all the recipes that may lead to constipation, feeling sick or stomach pain.
Evidence: may lead to constipation, feeling sick or stomach pain refers to iron > 20
SQL: SELECT T1.title FROM Recipe AS T1 INNER JOIN Nutrition AS T2 ON T1.recipe_id = T2.recipe_id WHERE T2.iron > 20
Database: cookbook
Tables: Ingredient, Recipe, Nutrition, Quantity
Columns (table index, column name): -1, *, 0, ingredient_id, 0, category, 0, name, 0, plural, 1, recipe_id, 1, title, 1, subtitle, 1, servings, 1, yield_unit, 1, prep_min, 1, cook_min, 1, stnd_min, 1, source, 1, intro, 1, directions, 2, recipe_id, 2, protein, 2, carbo, 2, alcohol, 2, total_fat, 2, sat_fat, 2, cholestrl, 2, sodium, 2, iron, 2, vitamin_c, 2, vitamin_a, 2, fiber, 2, pcnt_cal_carb, 2, pcnt_cal_fat, 2, pcnt_cal_prot, 2, calories, 3, quantity_id, 3, recipe_id, 3, ingredient_id, 3, max_qty, 3, min_qty, 3, unit, 3, preparation, 3, optional
Question: Which recipe is more beneficial in wound healing, "Raspberry Chiffon Pie" or "Fresh Apricot Bavarian"?
Evidence: Raspberry Chiffon Pie and Fresh Apricot Bavarian are title; vitamin_c is higher refers to MAX(vitamin_c)
SQL: SELECT DISTINCT CASE WHEN CASE WHEN T2.title = 'Raspberry Chiffon Pie' THEN T1.vitamin_c END > CASE WHEN T2.title = 'Fresh Apricot Bavarian' THEN T1.vitamin_c END THEN 'Raspberry Chiffon Pie' ELSE 'Fresh Apricot Bavarian' END AS "vitamin_c is higher" FROM Nutrition T1 INNER JOIN Recipe T2 ON T2.recipe_id = T1.recipe_id
Database: cookbook
Tables: Ingredient, Recipe, Nutrition, Quantity
Columns (table index, column name): -1, *, 0, ingredient_id, 0, category, 0, name, 0, plural, 1, recipe_id, 1, title, 1, subtitle, 1, servings, 1, yield_unit, 1, prep_min, 1, cook_min, 1, stnd_min, 1, source, 1, intro, 1, directions, 2, recipe_id, 2, protein, 2, carbo, 2, alcohol, 2, total_fat, 2, sat_fat, 2, cholestrl, 2, sodium, 2, iron, 2, vitamin_c, 2, vitamin_a, 2, fiber, 2, pcnt_cal_carb, 2, pcnt_cal_fat, 2, pcnt_cal_prot, 2, calories, 3, quantity_id, 3, recipe_id, 3, ingredient_id, 3, max_qty, 3, min_qty, 3, unit, 3, preparation, 3, optional
Question: Among the recipes that take more than 10 minutes to prepare, what is the title of the one with the most calories?
Evidence: more than 10 minutes to prepare refers to prep_min > 10; the most calories refers to MAX(calories)
SQL: SELECT T1.title FROM Recipe AS T1 INNER JOIN Nutrition AS T2 ON T1.recipe_id = T2.recipe_id WHERE T1.prep_min > 10 ORDER BY T2.calories DESC LIMIT 1
Database: cookbook
Tables: Ingredient, Recipe, Nutrition, Quantity
Columns (table index, column name): -1, *, 0, ingredient_id, 0, category, 0, name, 0, plural, 1, recipe_id, 1, title, 1, subtitle, 1, servings, 1, yield_unit, 1, prep_min, 1, cook_min, 1, stnd_min, 1, source, 1, intro, 1, directions, 2, recipe_id, 2, protein, 2, carbo, 2, alcohol, 2, total_fat, 2, sat_fat, 2, cholestrl, 2, sodium, 2, iron, 2, vitamin_c, 2, vitamin_a, 2, fiber, 2, pcnt_cal_carb, 2, pcnt_cal_fat, 2, pcnt_cal_prot, 2, calories, 3, quantity_id, 3, recipe_id, 3, ingredient_id, 3, max_qty, 3, min_qty, 3, unit, 3, preparation, 3, optional
Question: How many calories does the recipe "Raspberry Chiffon Pie" contain?
Evidence: Raspberry Chiffon Pie refers to title
SQL: SELECT T2.calories FROM Recipe AS T1 INNER JOIN Nutrition AS T2 ON T1.recipe_id = T2.recipe_id WHERE T1.title = 'Raspberry Chiffon Pie'
Database: cookbook
Tables: Ingredient, Recipe, Nutrition, Quantity
Columns (table index, column name): -1, *, 0, ingredient_id, 0, category, 0, name, 0, plural, 1, recipe_id, 1, title, 1, subtitle, 1, servings, 1, yield_unit, 1, prep_min, 1, cook_min, 1, stnd_min, 1, source, 1, intro, 1, directions, 2, recipe_id, 2, protein, 2, carbo, 2, alcohol, 2, total_fat, 2, sat_fat, 2, cholestrl, 2, sodium, 2, iron, 2, vitamin_c, 2, vitamin_a, 2, fiber, 2, pcnt_cal_carb, 2, pcnt_cal_fat, 2, pcnt_cal_prot, 2, calories, 3, quantity_id, 3, recipe_id, 3, ingredient_id, 3, max_qty, 3, min_qty, 3, unit, 3, preparation, 3, optional
Question: Is the ingredient "graham cracker crumbs" optional in the recipe "Raspberry Chiffon Pie"?
Evidence: 'graham cracker crumbs' is a name of an ingredient; 'Raspberry Chiffon Pie' refers to title
SQL: SELECT T2.optional FROM Recipe AS T1 INNER JOIN Quantity AS T2 ON T1.recipe_id = T2.recipe_id INNER JOIN Ingredient AS T3 ON T3.ingredient_id = T2.ingredient_id WHERE T1.title = 'Raspberry Chiffon Pie' AND T3.name = 'graham cracker crumbs'