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: What are the names of the establishments that met all the required standards for 4 consecutive years?
Evidence: establishment has the same meaning as business; score of 90 or more refers to score ≥ 90; year(date) = 2015; ; met all required standards for 4 consecutive years refers to COUNT(year(date)) = 4 where score = 100;
SQL: SELECT DISTINCT T4.name FROM ( SELECT T3.name, T3.years, row_number() OVER (PARTITION BY T3.name ORDER BY T3.years) AS rowNumber FROM ( SELECT DISTINCT name, STRFTIME('%Y', `date`) AS years FROM inspections AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T1.score = 100 ) AS T3 ) AS T4 GROUP BY T4.name, date(T4.years || '-01-01', '-' || (T4.rowNumber - 1) || ' years') HAVING COUNT(T4.years) = 4
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: Between 2014 to 2016, what is the average inpsection score of the establishment owned by Yiu Tim Chan in 808 Pacific Ave, San Francisco?
Evidence: average inspection score refers to avg(score); establishment owned by Yiu Tim Chan refers to business_id where owner_name = 'Yiu Tim Chan'; Between 2014 to 2016 refers to year(date) between 2014 and 2016; address = '808 Pacific Ave'; city = 'San Francisco';
SQL: SELECT AVG(T1.score) FROM inspections AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE STRFTIME('%Y', T1.`date`) BETWEEN '2014' AND '2016' AND T2.owner_name = 'Yiu Tim Chan' AND T2.address = '808 Pacific Ave' 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 average score of the establishments owned by the owner with the highest number of establishments?
Evidence: average score refers avg(score); owner with the highest number of establishments refers to owner_name where MAX(COUNT(business_id));
SQL: SELECT AVG(T1.score) FROM inspections AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id GROUP BY T2.owner_name ORDER BY COUNT(T2.business_id) 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: What is the name of the establishment with the highest number of low risk violations in 2014?
Evidence: establishment with the highest number of low risk violations refers to business_id where MAX(COUNT(risk_category = 'Low Risk')); year(date) = 2014;
SQL: SELECT T2.name FROM violations AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE STRFTIME('%Y', T1.`date`) = '2014' AND T1.risk_category = 'Low Risk' GROUP BY T2.name ORDER BY COUNT(T2.business_id) 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 top 5 owners with highest number of establishments, which owner has the highest number of high risk violations? Give the name of the owner.
Evidence: 5 owners with highest number of establishments refer to owner_name where MAX(COUNT(business_id)) LIMIT 5; the highest number of high risk violations refers to MAX(COUNT(risk_category = 'High Risk'));
SQL: SELECT T4.owner_name FROM violations AS T3 INNER JOIN businesses AS T4 ON T3.business_id = T4.business_id INNER JOIN ( SELECT T2.owner_name FROM violations AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id GROUP BY T2.owner_name ORDER BY COUNT(T1.business_id) DESC LIMIT 5 ) AS T5 ON T4.owner_name = T5.owner_name WHERE T3.risk_category = 'High Risk' GROUP BY T4.owner_name ORDER BY COUNT(T3.risk_category) 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: Which establishment has the highest number of inspections done? Give the name of the establishment and calculate for its average score per inspection.
Evidence: establishment refers to business_id; the highest number of inspections refers to MAX(COUNT(business_id)); avg(score);
SQL: SELECT T2.name, AVG(T1.score) FROM inspections AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id GROUP BY T2.name ORDER BY COUNT(T2.business_id) 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: How many eateries got highest inspection in 2013?
Evidence: eateries got highest inspection score in 2013 refer to business_id from inspections where score = 100 and year(date) = 2013;
SQL: SELECT COUNT(DISTINCT business_id) FROM inspections WHERE STRFTIME('%Y', `date`) = '2013' AND score = ( SELECT MAX(score) FROM inspections WHERE STRFTIME('%Y', `date`) = '2013' )
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 down the eateries' IDs with structural inspection type in February 2016.
Evidence: eateries' IDs refer to business_id; structural inspection type refers to inspections WHERE type = 'Structural Inspection'; in February 2016 refers to year(date) = 2016 and month(date) = 2;
SQL: SELECT business_id FROM inspections WHERE type = 'Structural Inspection' AND `date` LIKE '2016-02%'
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: How many eateries had low risk for violation with unpermitted food facility description?
Evidence: eateries represent business; low risk for violation refers to risk_category = 'Low Risk';
SQL: SELECT COUNT(DISTINCT business_id) FROM violations WHERE risk_category = 'Low Risk' AND description = 'Unpermitted food facility'
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: Provide eateries' IDs, risk categories and descriptions with violation ID of 103101.
Evidence: eateries' IDs refer to business_id; violation ID of 103101 refers to violation_type_id = '103101';
SQL: SELECT business_id, risk_category, description FROM violations WHERE violation_type_id = '103101'
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: When did eateries from San Bruno city get highest score in inspection?
Evidence: eateries represent business; highest score in inspection refers to score = 100;
SQL: SELECT T1.`date` FROM inspections AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T2.city = 'SAN BRUNO' 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: Describe the inspection types and violation descriptions under moderate risk category for ART's CAFÉ.
Evidence: ART's CAFÉ is the name of the business; moderate risk category refers to risk_category = 'Moderate Risk';
SQL: SELECT DISTINCT T2.type, T1.description 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 = 'ART''S CAFÉ' AND T1.risk_category = 'Moderate 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: 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: 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 inspection dates, scores and inspection types for the eateries with tax code AA.
Evidence: eateries with tax code AA refer to business_id where tax_code = 'AA';
SQL: SELECT T1.`date`, T1.score, T1.type FROM inspections AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T2.tax_code = 'AA'
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: Provide eateries' IDs, names and addresses which were inspected on 30th July, 2016.
Evidence: eateries' IDs inspected on 30th July, 2016 refer to business_id where business_id is not null and date = '2016-07-30';
SQL: SELECT DISTINCT T2.business_id, T2.name, T2.address FROM inspections AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T1.date = '2016-07-30'
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: Describe the violation dates, risk categories, descriptions and names of the eateries under Jade Chocolates LLC.
Evidence: eateries under Jade Chocolates LLC refer to business_id where owner_name = 'Jade Chocolates LLC';
SQL: SELECT T1.`date`, T1.risk_category, T1.description, T2.name FROM violations AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T2.owner_name = 'Jade Chocolates LLC'
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: Provide the names, risk categories and descriptions for the eateries with violation type ID of 103111.
Evidence: eateries refer to business_id;
SQL: SELECT T2.name, T1.risk_category, T1.description FROM violations AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T1.violation_type_id = '103111'
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 violations on 3rd June, 2014, describe any 5 names, located cities and tax codes of the eateries with high risk category.
Evidence: eateries with high risk category refer to business_id where risk_category = 'High Risk'; 3rd June, 2014 refers to date = '2014-06-03';
SQL: SELECT DISTINCT T2.name, T2.city, T2.tax_code FROM violations AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T1.risk_category = 'High Risk' AND T1.`date` = '2014-06-03' LIMIT 5
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 was the inspection type when El Aji Peruvian Restaurant got highest inspection score?
Evidence: El Aji Peruvian Restaurant is the name of the business; highest inspection score refers to MAX(score);
SQL: SELECT T1.type FROM inspections AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T2.name = 'El Aji Peruvian Restaurant' 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: Who were the owners of eateries which had highest health hazard by improper cooking time or temperatures?
Evidence: owners of eateries refer to owner_name; highest health hazard by improper cooking time or temperatures refers to risk_category = 'High Risk' and description = 'Improper cooking time or temperatures';
SQL: SELECT 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.description = 'Improper cooking time or temperatures'
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 eateries' names and addresses which had reinspection on 2nd February, 2015.
Evidence: eateries which had reinspection on 2nd February, 2015 refer to business_id where date = '2015-02-02' and type = 'Reinspection/Followup';
SQL: SELECT T2.name, T2.address FROM inspections AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T1.`date` = '2015-02-02' AND T1.type = 'Reinspection/Followup'
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 names and business certificates of the eateries which got inspection score under 50.
Evidence: eateries which got inspection score under 50 refer to business_id where score < 50;
SQL: SELECT T2.name, T2.business_id FROM inspections AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T1.score < 50
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: How many of the businesses are located at 1825 POST St #223, San Francisco?
Evidence: 1825 POST St #223 refers to address = '1825 POST St #223', San Francisco is the name of the city;
SQL: SELECT COUNT(business_id) FROM businesses WHERE address = '1825 POST St #223' AND 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: List down the owner's name with a zip code 94104.
Evidence: zip code 94104 refers to owner_zip = '94104';
SQL: SELECT DISTINCT owner_name FROM businesses WHERE owner_zip = '94104'
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 total number of businesses with a tax code H25?
SQL: SELECT COUNT(tax_code) FROM businesses WHERE tax_code = 'H25'
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 the violations in 2014, how many of them have a low risk category?
Evidence: in 2014 refers to year(date) = 2014; risk_category = 'Low Risk';
SQL: SELECT COUNT(risk_category) FROM violations WHERE STRFTIME('%Y', `date`) = '2014' AND risk_category = 'Low 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: Give the business ID and risk category of the business owned by San Francisco Madeleine, Inc.
Evidence: business owned by San Francisco Madeleine, Inc. refers to business_id where owner_name = 'San Francisco Madeleine, Inc.';
SQL: SELECT DISTINCT T2.business_id, T1.risk_category FROM violations AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T2.owner_name = 'San Francisco Madeleine, Inc.'