QIAN-ME/bird_schema_data huggingface dataset:
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 food_inspection
【Schema】
# Table: inspections
[
(business_id:INTEGER, Examples: [10, 24, 31]),
(score:INTEGER, Examples: [92, 94, 82]),
(date:DATE, Examples: [2014-01-14]),
(type:TEXT, Examples: [Routine - Unscheduled])
]
# Table: violations
[
(business_id:INTEGER, Examples: [10, 24, 31]),
(date:DATE, Examples: [2014-07-29]),
(violation_type_id:TEXT, Examples: [103129, 103144, 103119]),
(risk_category:TEXT, Examples: [Moderate Risk, Low Risk, High Risk]),
(description:TEXT, Examples: [Insufficient hot water or running water])
]
# Table: businesses
[
(business_id:INTEGER, Primary Key, Examples: [10, 24, 31]),
(name:TEXT, Examples: [Tiramisu Kitchen]),
(address:TEXT, Examples: [033 Belden Pl]),
(city:TEXT, Examples: [San Francisco, S.F., SAN FRANCISCO]),
(postal_code:TEXT, Examples: [94104, 94133, 94110]),
(latitude:REAL, Examples: [37.7911, 37.7929, 37.8072]),
(longitude:REAL, Examples: [-122.404, -122.403, -122.419]),
(phone_number:INTEGER, Examples: [14155345060, 14155823535, 14155344645]),
(tax_code:TEXT, Examples: [H24, H01, H25]),
(business_certificate:INTEGER, Examples: [779059, 352312, 346882]),
(application_date:DATE, Examples: [2001-10-10]),
(owner_name:TEXT, Examples: [Tiramisu LLC]),
(owner_address:TEXT, Examples: [33 Belden St]),
(owner_city:TEXT, Examples: [San Francisco, S.F., SAN FRANCISCO]),
(owner_state:TEXT, Examples: [CA, DC, WA]),
(owner_zip:TEXT, Examples: [94104, 94133, 94114])
]
【Foreign keys】
inspections.business_id=businesses.business_id
violations.business_id=businesses.business_id

    【Question】
    What was the type of inspection Tiramisu Kitchen had on 2014/1/14? Tiramisu Kitchen is the name of the business; inspection on 2014/1/14 refers to date = '2014-01-14';

    【Evidence】
    Tiramisu Kitchen is the name of the business; inspection on 2014/1/14 refers to date = '2014-01-14';

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT T1.type FROM inspections AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T1.`date` = '2014-01-14' AND T2.name = 'Tiramisu Kitchen'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 food_inspection
【Schema】
# Table: inspections
[
(business_id:INTEGER, Examples: [10, 24, 31]),
(score:INTEGER, Examples: [92, 94, 82]),
(date:DATE, Examples: [2014-01-14]),
(type:TEXT, Examples: [Routine - Unscheduled])
]
# Table: violations
[
(business_id:INTEGER, Examples: [10, 24, 31]),
(date:DATE, Examples: [2014-07-29]),
(violation_type_id:TEXT, Examples: [103129, 103144, 103119]),
(risk_category:TEXT, Examples: [Moderate Risk, Low Risk, High Risk]),
(description:TEXT, Examples: [Insufficient hot water or running water])
]
# Table: businesses
[
(business_id:INTEGER, Primary Key, Examples: [10, 24, 31]),
(name:TEXT, Examples: [Tiramisu Kitchen]),
(address:TEXT, Examples: [033 Belden Pl]),
(city:TEXT, Examples: [San Francisco, S.F., SAN FRANCISCO]),
(postal_code:TEXT, Examples: [94104, 94133, 94110]),
(latitude:REAL, Examples: [37.7911, 37.7929, 37.8072]),
(longitude:REAL, Examples: [-122.404, -122.403, -122.419]),
(phone_number:INTEGER, Examples: [14155345060, 14155823535, 14155344645]),
(tax_code:TEXT, Examples: [H24, H01, H25]),
(business_certificate:INTEGER, Examples: [779059, 352312, 346882]),
(application_date:DATE, Examples: [2001-10-10]),
(owner_name:TEXT, Examples: [Tiramisu LLC]),
(owner_address:TEXT, Examples: [33 Belden St]),
(owner_city:TEXT, Examples: [San Francisco, S.F., SAN FRANCISCO]),
(owner_state:TEXT, Examples: [CA, DC, WA]),
(owner_zip:TEXT, Examples: [94104, 94133, 94114])
]
【Foreign keys】
inspections.business_id=businesses.business_id
violations.business_id=businesses.business_id

    【Question】
    How many low risk violations were found in the inspection on 2014/1/14 for Tiramisu Kitchen? Tiramisu Kitchen is the name of the business; inspection on 2014/1/14 refers to date = '2014-01-14'; low risk violations refer to risk_category = 'Low Risk';

    【Evidence】
    Tiramisu Kitchen is the name of the business; inspection on 2014/1/14 refers to date = '2014-01-14'; low risk violations refer to risk_category = 'Low Risk';

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT COUNT(T1.business_id) FROM violations AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T1.`date` = '2014-01-14' AND T2.name = 'Tiramisu Kitchen' AND T1.risk_category = 'Low Risk'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 food_inspection
【Schema】
# Table: inspections
[
(business_id:INTEGER, Examples: [10, 24, 31]),
(score:INTEGER, Examples: [92, 94, 82]),
(date:DATE, Examples: [2014-01-14]),
(type:TEXT, Examples: [Routine - Unscheduled])
]
# Table: violations
[
(business_id:INTEGER, Examples: [10, 24, 31]),
(date:DATE, Examples: [2014-07-29]),
(violation_type_id:TEXT, Examples: [103129, 103144, 103119]),
(risk_category:TEXT, Examples: [Moderate Risk, Low Risk, High Risk]),
(description:TEXT, Examples: [Insufficient hot water or running water])
]
# Table: businesses
[
(business_id:INTEGER, Primary Key, Examples: [10, 24, 31]),
(name:TEXT, Examples: [Tiramisu Kitchen]),
(address:TEXT, Examples: [033 Belden Pl]),
(city:TEXT, Examples: [San Francisco, S.F., SAN FRANCISCO]),
(postal_code:TEXT, Examples: [94104, 94133, 94110]),
(latitude:REAL, Examples: [37.7911, 37.7929, 37.8072]),
(longitude:REAL, Examples: [-122.404, -122.403, -122.419]),
(phone_number:INTEGER, Examples: [14155345060, 14155823535, 14155344645]),
(tax_code:TEXT, Examples: [H24, H01, H25]),
(business_certificate:INTEGER, Examples: [779059, 352312, 346882]),
(application_date:DATE, Examples: [2001-10-10]),
(owner_name:TEXT, Examples: [Tiramisu LLC]),
(owner_address:TEXT, Examples: [33 Belden St]),
(owner_city:TEXT, Examples: [San Francisco, S.F., SAN FRANCISCO]),
(owner_state:TEXT, Examples: [CA, DC, WA]),
(owner_zip:TEXT, Examples: [94104, 94133, 94114])
]
【Foreign keys】
inspections.business_id=businesses.business_id
violations.business_id=businesses.business_id

    【Question】
    Please list the names of the restaurants that had a low risk violation in inspections in 2014. inspection in 2014 refers to year(date) = 2014; low risk violations refer to risk_category = 'Low Risk';

    【Evidence】
    inspection in 2014 refers to year(date) = 2014; low risk violations refer to risk_category = 'Low Risk';

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT DISTINCT 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'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 food_inspection
【Schema】
# Table: inspections
[
(business_id:INTEGER, Examples: [10, 24, 31]),
(score:INTEGER, Examples: [92, 94, 82]),
(date:DATE, Examples: [2014-01-14]),
(type:TEXT, Examples: [Routine - Unscheduled])
]
# Table: violations
[
(business_id:INTEGER, Examples: [10, 24, 31]),
(date:DATE, Examples: [2014-07-29]),
(violation_type_id:TEXT, Examples: [103129, 103144, 103119]),
(risk_category:TEXT, Examples: [Moderate Risk, Low Risk, High Risk]),
(description:TEXT, Examples: [Insufficient hot water or running water])
]
# Table: businesses
[
(business_id:INTEGER, Primary Key, Examples: [10, 24, 31]),
(name:TEXT, Examples: [Tiramisu Kitchen]),
(address:TEXT, Examples: [033 Belden Pl]),
(city:TEXT, Examples: [San Francisco, S.F., SAN FRANCISCO]),
(postal_code:TEXT, Examples: [94104, 94133, 94110]),
(latitude:REAL, Examples: [37.7911, 37.7929, 37.8072]),
(longitude:REAL, Examples: [-122.404, -122.403, -122.419]),
(phone_number:INTEGER, Examples: [14155345060, 14155823535, 14155344645]),
(tax_code:TEXT, Examples: [H24, H01, H25]),
(business_certificate:INTEGER, Examples: [779059, 352312, 346882]),
(application_date:DATE, Examples: [2001-10-10]),
(owner_name:TEXT, Examples: [Tiramisu LLC]),
(owner_address:TEXT, Examples: [33 Belden St]),
(owner_city:TEXT, Examples: [San Francisco, S.F., SAN FRANCISCO]),
(owner_state:TEXT, Examples: [CA, DC, WA]),
(owner_zip:TEXT, Examples: [94104, 94133, 94114])
]
【Foreign keys】
inspections.business_id=businesses.business_id
violations.business_id=businesses.business_id

    【Question】
    What is the description of the low risk violation of Tiramisu Kitchen on 2014/1/14? Tiramisu Kitchen is the name of the business; 2014/1/14 refers to date = '2014-01-14'; low risk violations refer to risk_category = 'Low Risk';

    【Evidence】
    Tiramisu Kitchen is the name of the business; 2014/1/14 refers to date = '2014-01-14'; low risk violations refer to risk_category = 'Low Risk';

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT T1.description FROM violations AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T1.`date` = '2014-01-14' AND T2.name = 'Tiramisu Kitchen' AND T1.risk_category = 'Low Risk'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 food_inspection
【Schema】
# Table: inspections
[
(business_id:INTEGER, Examples: [10, 24, 31]),
(score:INTEGER, Examples: [92, 94, 82]),
(date:DATE, Examples: [2014-01-14]),
(type:TEXT, Examples: [Routine - Unscheduled])
]
# Table: violations
[
(business_id:INTEGER, Examples: [10, 24, 31]),
(date:DATE, Examples: [2014-07-29]),
(violation_type_id:TEXT, Examples: [103129, 103144, 103119]),
(risk_category:TEXT, Examples: [Moderate Risk, Low Risk, High Risk]),
(description:TEXT, Examples: [Insufficient hot water or running water])
]
# Table: businesses
[
(business_id:INTEGER, Primary Key, Examples: [10, 24, 31]),
(name:TEXT, Examples: [Tiramisu Kitchen]),
(address:TEXT, Examples: [033 Belden Pl]),
(city:TEXT, Examples: [San Francisco, S.F., SAN FRANCISCO]),
(postal_code:TEXT, Examples: [94104, 94133, 94110]),
(latitude:REAL, Examples: [37.7911, 37.7929, 37.8072]),
(longitude:REAL, Examples: [-122.404, -122.403, -122.419]),
(phone_number:INTEGER, Examples: [14155345060, 14155823535, 14155344645]),
(tax_code:TEXT, Examples: [H24, H01, H25]),
(business_certificate:INTEGER, Examples: [779059, 352312, 346882]),
(application_date:DATE, Examples: [2001-10-10]),
(owner_name:TEXT, Examples: [Tiramisu LLC]),
(owner_address:TEXT, Examples: [33 Belden St]),
(owner_city:TEXT, Examples: [San Francisco, S.F., SAN FRANCISCO]),
(owner_state:TEXT, Examples: [CA, DC, WA]),
(owner_zip:TEXT, Examples: [94104, 94133, 94114])
]
【Foreign keys】
inspections.business_id=businesses.business_id
violations.business_id=businesses.business_id

    【Question】
    Please list the descriptions of all the high risk violations of Tiramisu Kitchen. Tiramisu Kitchen is the name of the business; high risk violations refer to risk_category = 'High Risk';

    【Evidence】
    Tiramisu Kitchen is the name of the business; high risk violations refer to risk_category = 'High Risk';

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT DISTINCT T1.description FROM violations AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T1.risk_category = 'High Risk' AND T2.name = 'Tiramisu Kitchen'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 food_inspection
【Schema】
# Table: inspections
[
(business_id:INTEGER, Examples: [10, 24, 31]),
(score:INTEGER, Examples: [92, 94, 82]),
(date:DATE, Examples: [2014-01-14]),
(type:TEXT, Examples: [Routine - Unscheduled])
]
# Table: violations
[
(business_id:INTEGER, Examples: [10, 24, 31]),
(date:DATE, Examples: [2014-07-29]),
(violation_type_id:TEXT, Examples: [103129, 103144, 103119]),
(risk_category:TEXT, Examples: [Moderate Risk, Low Risk, High Risk]),
(description:TEXT, Examples: [Insufficient hot water or running water])
]
# Table: businesses
[
(business_id:INTEGER, Primary Key, Examples: [10, 24, 31]),
(name:TEXT, Examples: [Tiramisu Kitchen]),
(address:TEXT, Examples: [033 Belden Pl]),
(city:TEXT, Examples: [San Francisco, S.F., SAN FRANCISCO]),
(postal_code:TEXT, Examples: [94104, 94133, 94110]),
(latitude:REAL, Examples: [37.7911, 37.7929, 37.8072]),
(longitude:REAL, Examples: [-122.404, -122.403, -122.419]),
(phone_number:INTEGER, Examples: [14155345060, 14155823535, 14155344645]),
(tax_code:TEXT, Examples: [H24, H01, H25]),
(business_certificate:INTEGER, Examples: [779059, 352312, 346882]),
(application_date:DATE, Examples: [2001-10-10]),
(owner_name:TEXT, Examples: [Tiramisu LLC]),
(owner_address:TEXT, Examples: [33 Belden St]),
(owner_city:TEXT, Examples: [San Francisco, S.F., SAN FRANCISCO]),
(owner_state:TEXT, Examples: [CA, DC, WA]),
(owner_zip:TEXT, Examples: [94104, 94133, 94114])
]
【Foreign keys】
inspections.business_id=businesses.business_id
violations.business_id=businesses.business_id

    【Question】
    How many routine inspections did Tiramisu Kitchen have? Tiramisu Kitchen is the name of the business; routine inspections refer to type = 'Routine - Unscheduled';

    【Evidence】
    Tiramisu Kitchen is the name of the business; routine inspections refer to type = 'Routine - Unscheduled';

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT COUNT(T1.business_id) FROM inspections AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T1.type = 'Routine - Unscheduled' AND T2.name = 'Tiramisu Kitchen'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 food_inspection
【Schema】
# Table: inspections
[
(business_id:INTEGER, Examples: [10, 24, 31]),
(score:INTEGER, Examples: [92, 94, 82]),
(date:DATE, Examples: [2014-01-14]),
(type:TEXT, Examples: [Routine - Unscheduled])
]
# Table: violations
[
(business_id:INTEGER, Examples: [10, 24, 31]),
(date:DATE, Examples: [2014-07-29]),
(violation_type_id:TEXT, Examples: [103129, 103144, 103119]),
(risk_category:TEXT, Examples: [Moderate Risk, Low Risk, High Risk]),
(description:TEXT, Examples: [Insufficient hot water or running water])
]
# Table: businesses
[
(business_id:INTEGER, Primary Key, Examples: [10, 24, 31]),
(name:TEXT, Examples: [Tiramisu Kitchen]),
(address:TEXT, Examples: [033 Belden Pl]),
(city:TEXT, Examples: [San Francisco, S.F., SAN FRANCISCO]),
(postal_code:TEXT, Examples: [94104, 94133, 94110]),
(latitude:REAL, Examples: [37.7911, 37.7929, 37.8072]),
(longitude:REAL, Examples: [-122.404, -122.403, -122.419]),
(phone_number:INTEGER, Examples: [14155345060, 14155823535, 14155344645]),
(tax_code:TEXT, Examples: [H24, H01, H25]),
(business_certificate:INTEGER, Examples: [779059, 352312, 346882]),
(application_date:DATE, Examples: [2001-10-10]),
(owner_name:TEXT, Examples: [Tiramisu LLC]),
(owner_address:TEXT, Examples: [33 Belden St]),
(owner_city:TEXT, Examples: [San Francisco, S.F., SAN FRANCISCO]),
(owner_state:TEXT, Examples: [CA, DC, WA]),
(owner_zip:TEXT, Examples: [94104, 94133, 94114])
]
【Foreign keys】
inspections.business_id=businesses.business_id
violations.business_id=businesses.business_id

    【Question】
    Among the routine inspections of Tiramisu Kitchen, how many of them have a score of over 70? Tiramisu Kitchen is the name of the business; routine inspections refer to type = 'Routine - Unscheduled'; score of over 70 refers to score > 70;

    【Evidence】
    Tiramisu Kitchen is the name of the business; routine inspections refer to type = 'Routine - Unscheduled'; score of over 70 refers to score > 70;

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT COUNT(T2.business_id) FROM inspections AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T2.name = 'Tiramisu Kitchen' AND T1.type = 'Routine - Unscheduled' AND T1.score > 70
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 food_inspection
【Schema】
# Table: inspections
[
(business_id:INTEGER, Examples: [10, 24, 31]),
(score:INTEGER, Examples: [92, 94, 82]),
(date:DATE, Examples: [2014-01-14]),
(type:TEXT, Examples: [Routine - Unscheduled])
]
# Table: violations
[
(business_id:INTEGER, Examples: [10, 24, 31]),
(date:DATE, Examples: [2014-07-29]),
(violation_type_id:TEXT, Examples: [103129, 103144, 103119]),
(risk_category:TEXT, Examples: [Moderate Risk, Low Risk, High Risk]),
(description:TEXT, Examples: [Insufficient hot water or running water])
]
# Table: businesses
[
(business_id:INTEGER, Primary Key, Examples: [10, 24, 31]),
(name:TEXT, Examples: [Tiramisu Kitchen]),
(address:TEXT, Examples: [033 Belden Pl]),
(city:TEXT, Examples: [San Francisco, S.F., SAN FRANCISCO]),
(postal_code:TEXT, Examples: [94104, 94133, 94110]),
(latitude:REAL, Examples: [37.7911, 37.7929, 37.8072]),
(longitude:REAL, Examples: [-122.404, -122.403, -122.419]),
(phone_number:INTEGER, Examples: [14155345060, 14155823535, 14155344645]),
(tax_code:TEXT, Examples: [H24, H01, H25]),
(business_certificate:INTEGER, Examples: [779059, 352312, 346882]),
(application_date:DATE, Examples: [2001-10-10]),
(owner_name:TEXT, Examples: [Tiramisu LLC]),
(owner_address:TEXT, Examples: [33 Belden St]),
(owner_city:TEXT, Examples: [San Francisco, S.F., SAN FRANCISCO]),
(owner_state:TEXT, Examples: [CA, DC, WA]),
(owner_zip:TEXT, Examples: [94104, 94133, 94114])
]
【Foreign keys】
inspections.business_id=businesses.business_id
violations.business_id=businesses.business_id

    【Question】
    Which restaurant had more low risk violation in inspections, Tiramisu Kitchen or OMNI S.F. Hotel - 2nd Floor Pantry? Tiramisu Kitchen and OMNI S.F. Hotel - 2nd Floor Pantry are names of the business; more low risk violations refer to MAX(COUNT(risk_category = 'Low Risk'));

    【Evidence】
    Tiramisu Kitchen and OMNI S.F. Hotel - 2nd Floor Pantry are names of the business; more low risk violations refer to MAX(COUNT(risk_category = 'Low Risk'));

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT CASE WHEN SUM(CASE WHEN T2.name = 'OMNI S.F. Hotel - 2nd Floor Pantry' THEN 1 ELSE 0 END) > SUM(CASE WHEN T2.name = 'Tiramisu Kitchen' THEN 1 ELSE 0 END) THEN 'OMNI S.F. Hotel - 2nd Floor Pantry' ELSE 'Tiramisu Kitchen' END AS result FROM violations AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T1.risk_category = 'Low Risk'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 food_inspection
【Schema】
# Table: inspections
[
(business_id:INTEGER, Examples: [10, 24, 31]),
(score:INTEGER, Examples: [92, 94, 82]),
(date:DATE, Examples: [2014-01-14]),
(type:TEXT, Examples: [Routine - Unscheduled])
]
# Table: violations
[
(business_id:INTEGER, Examples: [10, 24, 31]),
(date:DATE, Examples: [2014-07-29]),
(violation_type_id:TEXT, Examples: [103129, 103144, 103119]),
(risk_category:TEXT, Examples: [Moderate Risk, Low Risk, High Risk]),
(description:TEXT, Examples: [Insufficient hot water or running water])
]
# Table: businesses
[
(business_id:INTEGER, Primary Key, Examples: [10, 24, 31]),
(name:TEXT, Examples: [Tiramisu Kitchen]),
(address:TEXT, Examples: [033 Belden Pl]),
(city:TEXT, Examples: [San Francisco, S.F., SAN FRANCISCO]),
(postal_code:TEXT, Examples: [94104, 94133, 94110]),
(latitude:REAL, Examples: [37.7911, 37.7929, 37.8072]),
(longitude:REAL, Examples: [-122.404, -122.403, -122.419]),
(phone_number:INTEGER, Examples: [14155345060, 14155823535, 14155344645]),
(tax_code:TEXT, Examples: [H24, H01, H25]),
(business_certificate:INTEGER, Examples: [779059, 352312, 346882]),
(application_date:DATE, Examples: [2001-10-10]),
(owner_name:TEXT, Examples: [Tiramisu LLC]),
(owner_address:TEXT, Examples: [33 Belden St]),
(owner_city:TEXT, Examples: [San Francisco, S.F., SAN FRANCISCO]),
(owner_state:TEXT, Examples: [CA, DC, WA]),
(owner_zip:TEXT, Examples: [94104, 94133, 94114])
]
【Foreign keys】
inspections.business_id=businesses.business_id
violations.business_id=businesses.business_id

    【Question】
    How many high risk violations do the restaurants in San Francisco have in total? restaurants in San Francisco refer to business_id where city in ('San Francisco', 'SF', 'S.F.', 'SAN FRANCISCO'); high risk violations refer to risk_category = 'High Risk';

    【Evidence】
    restaurants in San Francisco refer to business_id where city in ('San Francisco', 'SF', 'S.F.', 'SAN FRANCISCO'); high risk violations refer to risk_category = 'High Risk';

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT COUNT(T2.business_id) FROM violations AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T2.city IN ('San Francisco', 'SF', 'S.F.', 'SAN FRANCISCO') AND T1.risk_category = 'High Risk'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 food_inspection
【Schema】
# Table: inspections
[
(business_id:INTEGER, Examples: [10, 24, 31]),
(score:INTEGER, Examples: [92, 94, 82]),
(date:DATE, Examples: [2014-01-14]),
(type:TEXT, Examples: [Routine - Unscheduled])
]
# Table: violations
[
(business_id:INTEGER, Examples: [10, 24, 31]),
(date:DATE, Examples: [2014-07-29]),
(violation_type_id:TEXT, Examples: [103129, 103144, 103119]),
(risk_category:TEXT, Examples: [Moderate Risk, Low Risk, High Risk]),
(description:TEXT, Examples: [Insufficient hot water or running water])
]
# Table: businesses
[
(business_id:INTEGER, Primary Key, Examples: [10, 24, 31]),
(name:TEXT, Examples: [Tiramisu Kitchen]),
(address:TEXT, Examples: [033 Belden Pl]),
(city:TEXT, Examples: [San Francisco, S.F., SAN FRANCISCO]),
(postal_code:TEXT, Examples: [94104, 94133, 94110]),
(latitude:REAL, Examples: [37.7911, 37.7929, 37.8072]),
(longitude:REAL, Examples: [-122.404, -122.403, -122.419]),
(phone_number:INTEGER, Examples: [14155345060, 14155823535, 14155344645]),
(tax_code:TEXT, Examples: [H24, H01, H25]),
(business_certificate:INTEGER, Examples: [779059, 352312, 346882]),
(application_date:DATE, Examples: [2001-10-10]),
(owner_name:TEXT, Examples: [Tiramisu LLC]),
(owner_address:TEXT, Examples: [33 Belden St]),
(owner_city:TEXT, Examples: [San Francisco, S.F., SAN FRANCISCO]),
(owner_state:TEXT, Examples: [CA, DC, WA]),
(owner_zip:TEXT, Examples: [94104, 94133, 94114])
]
【Foreign keys】
inspections.business_id=businesses.business_id
violations.business_id=businesses.business_id

    【Question】
    Which restaurant has the highest total number of high risk violations? the highest total number of high risk violations refer to MAX(COUNT(risk_category = 'High Risk'));

    【Evidence】
    the highest total number of high risk violations refer to MAX(COUNT(risk_category = 'High Risk'));

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT T2.name FROM violations AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T1.risk_category = 'High Risk' GROUP BY T2.name ORDER BY COUNT(T2.name) DESC LIMIT 1