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】
    Give the address of the business with the most number of the low risk violations. the most number of the low risk violations refers to MAX(COUNT(business_id)) where risk_category = 'Low Risk' ;

    【Evidence】
    the most number of the low risk violations refers to MAX(COUNT(business_id)) where 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 T2.address FROM violations AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T1.risk_category = 'Low Risk' GROUP BY T2.address ORDER BY COUNT(T1.business_id) DESC LIMIT 1
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 business was the first one to get a low risk violation because of "Permit license or inspection report not posted"? Give the name of the business. low risk violation because of "Permit license or inspection report not posted" refers to risk_category = 'Low Risk' where description = 'Permit license or inspection report not posted'; business was the first one refers to name where MIN(date);

    【Evidence】
    low risk violation because of "Permit license or inspection report not posted" refers to risk_category = 'Low Risk' where description = 'Permit license or inspection report not posted'; business was the first one refers to name where MIN(date);

    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.`date` = ( SELECT MIN(`date`) FROM violations WHERE risk_category = 'Low Risk' AND description = 'Permit license or inspection report not posted' ) AND T1.risk_category = 'Low Risk' AND T1.description = 'Permit license or inspection report not posted'
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】
    For the business which got the most number of violations, how many inspections did it have?

    【Evidence】
    

    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 inspections AS T2 ON T1.business_id = T2.business_id GROUP BY T1.business_id ORDER BY COUNT(T1.business_id) DESC LIMIT 1
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】
    For the business whose business certificate number is 304977, how many violations did it have on 2013/10/7? date = '2013-10-07';

    【Evidence】
    date = '2013-10-07';

    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 T2.business_certificate = '304977' AND T1.`date` = '2013-10-07'
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 average score for "Chairman Bao" in all its unscheduled routine inspections? DIVIDE(SUM(score where type = 'Routine - Unscheduled' and name = 'Chairman Bao'), COUNT(type = 'Routine - Unscheduled' where name = 'Chairman Bao'));

    【Evidence】
    DIVIDE(SUM(score where type = 'Routine - Unscheduled' and name = 'Chairman Bao'), COUNT(type = 'Routine - Unscheduled' where name = 'Chairman Bao'));

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

SQL: SELECT CAST(SUM(CASE WHEN T2.name = 'Chairman Bao' THEN T1.score ELSE 0 END) AS REAL) / COUNT(CASE WHEN T1.type = 'Routine - Unscheduled' THEN T1.score ELSE 0 END) FROM inspections AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id
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 percentage of the violations for "Melody Lounge" are moderate risks? DIVIDE(COUNT(risk_category = 'Moderate Risk' where name = 'Melody Lounge'), COUNT(business_id where name = 'Melody Lounge')) as percentage;

    【Evidence】
    DIVIDE(COUNT(risk_category = 'Moderate Risk' where name = 'Melody Lounge'), COUNT(business_id where name = 'Melody Lounge')) as percentage;

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

SQL: SELECT CAST(SUM(CASE WHEN T2.risk_category = 'Moderate Risk' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T2.business_id) FROM businesses AS T1 INNER JOIN violations AS T2 ON T1.business_id = T2.business_id WHERE T1.name = 'Melody Lounge'
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 eateries are located in Hayward? eateries in Hayward refer city = 'HAYWARD';

    【Evidence】
    eateries in Hayward refer city = 'HAYWARD';

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

SQL: SELECT COUNT(business_id) FROM businesses WHERE city = 'HAYWARD'
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 establishments have an inspection score of no more than 50? establishments have the same meaning as businesses; inspection score of no more than 50 refers to score < 50;

    【Evidence】
    establishments have the same meaning as businesses; inspection score of no more than 50 refers to score < 50;

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

SQL: SELECT COUNT(DISTINCT business_id) FROM inspections WHERE score < 50
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 eateries applied in 2012? eateries applied in 2012 refer to business_id where application_date between '2012-01-01' and '2012-12-31';

    【Evidence】
    eateries applied in 2012 refer to business_id where application_date between '2012-01-01' and '2012-12-31';

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

SQL: SELECT COUNT(business_id) FROM businesses WHERE STRFTIME('%Y', application_date) = '2012'
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 foodborne illness investigations were done in 2014? foodborne illness investigations refer to inspections where type = 'Foodborne Illness Investigation'; investigations in 2014 refers to date between '2014-01-01' and '2014-12-31';

    【Evidence】
    foodborne illness investigations refer to inspections where type = 'Foodborne Illness Investigation'; investigations in 2014 refers to date between '2014-01-01' and '2014-12-31';

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

SQL: SELECT COUNT(business_id) FROM inspections WHERE STRFTIME('%Y', `date`) = '2014' AND type = 'Foodborne Illness Investigation'