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】 law_episode
【Schema】
# Table: Credit
[
(episode_id:TEXT, Primary Key, Examples: [tt0629146, tt0629149, tt0629153]),
(person_id:TEXT, Primary Key, Examples: [nm0000973, nm0001583, nm0001832]),
(category:TEXT, Examples: [Additional Crew]),
(role:TEXT, Examples: [technical advisor]),
(credited:TEXT, Examples: [true, false])
]
# Table: Person
[
(person_id:TEXT, Primary Key, Examples: [nm0000210, nm0000973, nm0001346]),
(name:TEXT, Examples: [Julia Roberts, Rene Balcer, Billy Fox]),
(birthdate:DATE, Examples: [1967-10-28]),
(birth_name:TEXT, Examples: [Julia Fiona Roberts]),
(birth_place:TEXT, Examples: [Smyrna, Montreal, Harrisburg]),
(birth_region:TEXT, Examples: [Georgia, Quebec, Pennsylvania]),
(birth_country:TEXT, Examples: [USA, Canada, England]),
(height_meters:REAL, Examples: [1.73, 1.88, 1.93]),
(nickname:TEXT, Examples: [Jules, Gus, Ed])
]
# Table: Award
[
(award_id:INTEGER, Primary Key, Examples: [258, 259, 260]),
(organization:TEXT),
(year:INTEGER, Examples: [1999, 2000]),
(award_category:TEXT, Examples: [Monitor, Primetime Emmy, Silver Gavel Award]),
(award:TEXT),
(series:TEXT, Examples: [Law and Order]),
(episode_id:TEXT, Examples: [tt0629149, tt0629398, tt0629248]),
(person_id:TEXT, Examples: [nm0937725, nm0792309, nm0049569]),
(role:TEXT, Examples: [Katrina Ludlow, production mixer, re-recording mixer]),
(result:TEXT, Examples: [Winner, Nominee])
]
# Table: Vote
[
(episode_id:TEXT, Examples: [tt0629204, tt0629228, tt0629170]),
(stars:INTEGER, Examples: [10, 9, 8]),
(votes:INTEGER, Examples: [36, 39, 64]),
(percent:REAL, Examples: [17.7, 19.2, 31.5])
]
# Table: Episode
[
(episode_id:TEXT, Primary Key, Examples: [tt0629146, tt0629149, tt0629153]),
(series:TEXT, Examples: [Law and Order]),
(season:INTEGER, Examples: [9]),
(episode:INTEGER, Examples: [1, 2, 3]),
(number_in_series:INTEGER, Examples: [182, 183, 184]),
(title:TEXT, Examples: [Cherished, DWB, Bait]),
(summary:TEXT),
(air_date:DATE, Examples: [1998-09-23]),
(episode_image:TEXT),
(rating:REAL, Examples: [7.9, 7.6, 8.2]),
(votes:INTEGER, Examples: [203, 177, 159])
]
# Table: Keyword
[
(episode_id:TEXT, Primary Key, Examples: [tt0629239, tt0629397, tt0629420]),
(keyword:TEXT, Primary Key, Examples: [nun, priest, police officer])
]
【Foreign keys】
Credit.episode_id=Episode.episode_id
Credit.person_id=Person.person_id
Award.episode_id=Episode.episode_id
Award.person_id=Person.person_id
Vote.episode_id=Episode.episode_id
Keyword.episode_id=Episode.episode_id

    【Question】
    What are the keywords of the "Shield" episode? "Shield" episode refers to title = 'Shield'

    【Evidence】
    "Shield" episode refers to title = 'Shield'

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

SQL: SELECT T2.keyword FROM Episode AS T1 INNER JOIN Keyword AS T2 ON T1.episode_id = T2.episode_id WHERE T1.title = 'Shield'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 law_episode
【Schema】
# Table: Credit
[
(episode_id:TEXT, Primary Key, Examples: [tt0629146, tt0629149, tt0629153]),
(person_id:TEXT, Primary Key, Examples: [nm0000973, nm0001583, nm0001832]),
(category:TEXT, Examples: [Additional Crew]),
(role:TEXT, Examples: [technical advisor]),
(credited:TEXT, Examples: [true, false])
]
# Table: Person
[
(person_id:TEXT, Primary Key, Examples: [nm0000210, nm0000973, nm0001346]),
(name:TEXT, Examples: [Julia Roberts, Rene Balcer, Billy Fox]),
(birthdate:DATE, Examples: [1967-10-28]),
(birth_name:TEXT, Examples: [Julia Fiona Roberts]),
(birth_place:TEXT, Examples: [Smyrna, Montreal, Harrisburg]),
(birth_region:TEXT, Examples: [Georgia, Quebec, Pennsylvania]),
(birth_country:TEXT, Examples: [USA, Canada, England]),
(height_meters:REAL, Examples: [1.73, 1.88, 1.93]),
(nickname:TEXT, Examples: [Jules, Gus, Ed])
]
# Table: Award
[
(award_id:INTEGER, Primary Key, Examples: [258, 259, 260]),
(organization:TEXT),
(year:INTEGER, Examples: [1999, 2000]),
(award_category:TEXT, Examples: [Monitor, Primetime Emmy, Silver Gavel Award]),
(award:TEXT),
(series:TEXT, Examples: [Law and Order]),
(episode_id:TEXT, Examples: [tt0629149, tt0629398, tt0629248]),
(person_id:TEXT, Examples: [nm0937725, nm0792309, nm0049569]),
(role:TEXT, Examples: [Katrina Ludlow, production mixer, re-recording mixer]),
(result:TEXT, Examples: [Winner, Nominee])
]
# Table: Vote
[
(episode_id:TEXT, Examples: [tt0629204, tt0629228, tt0629170]),
(stars:INTEGER, Examples: [10, 9, 8]),
(votes:INTEGER, Examples: [36, 39, 64]),
(percent:REAL, Examples: [17.7, 19.2, 31.5])
]
# Table: Episode
[
(episode_id:TEXT, Primary Key, Examples: [tt0629146, tt0629149, tt0629153]),
(series:TEXT, Examples: [Law and Order]),
(season:INTEGER, Examples: [9]),
(episode:INTEGER, Examples: [1, 2, 3]),
(number_in_series:INTEGER, Examples: [182, 183, 184]),
(title:TEXT, Examples: [Cherished, DWB, Bait]),
(summary:TEXT),
(air_date:DATE, Examples: [1998-09-23]),
(episode_image:TEXT),
(rating:REAL, Examples: [7.9, 7.6, 8.2]),
(votes:INTEGER, Examples: [203, 177, 159])
]
# Table: Keyword
[
(episode_id:TEXT, Primary Key, Examples: [tt0629239, tt0629397, tt0629420]),
(keyword:TEXT, Primary Key, Examples: [nun, priest, police officer])
]
【Foreign keys】
Credit.episode_id=Episode.episode_id
Credit.person_id=Person.person_id
Award.episode_id=Episode.episode_id
Award.person_id=Person.person_id
Vote.episode_id=Episode.episode_id
Keyword.episode_id=Episode.episode_id

    【Question】
    What is the title of the episode with the highest number of keywords? the highest number of keywords refers to max(count(keyword))

    【Evidence】
    the highest number of keywords refers to max(count(keyword))

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

SQL: SELECT T1.title FROM Episode AS T1 INNER JOIN Keyword AS T2 ON T1.episode_id = T2.episode_id GROUP BY T1.episode_id ORDER BY COUNT(T2.keyword) DESC LIMIT 1
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 law_episode
【Schema】
# Table: Credit
[
(episode_id:TEXT, Primary Key, Examples: [tt0629146, tt0629149, tt0629153]),
(person_id:TEXT, Primary Key, Examples: [nm0000973, nm0001583, nm0001832]),
(category:TEXT, Examples: [Additional Crew]),
(role:TEXT, Examples: [technical advisor]),
(credited:TEXT, Examples: [true, false])
]
# Table: Person
[
(person_id:TEXT, Primary Key, Examples: [nm0000210, nm0000973, nm0001346]),
(name:TEXT, Examples: [Julia Roberts, Rene Balcer, Billy Fox]),
(birthdate:DATE, Examples: [1967-10-28]),
(birth_name:TEXT, Examples: [Julia Fiona Roberts]),
(birth_place:TEXT, Examples: [Smyrna, Montreal, Harrisburg]),
(birth_region:TEXT, Examples: [Georgia, Quebec, Pennsylvania]),
(birth_country:TEXT, Examples: [USA, Canada, England]),
(height_meters:REAL, Examples: [1.73, 1.88, 1.93]),
(nickname:TEXT, Examples: [Jules, Gus, Ed])
]
# Table: Award
[
(award_id:INTEGER, Primary Key, Examples: [258, 259, 260]),
(organization:TEXT),
(year:INTEGER, Examples: [1999, 2000]),
(award_category:TEXT, Examples: [Monitor, Primetime Emmy, Silver Gavel Award]),
(award:TEXT),
(series:TEXT, Examples: [Law and Order]),
(episode_id:TEXT, Examples: [tt0629149, tt0629398, tt0629248]),
(person_id:TEXT, Examples: [nm0937725, nm0792309, nm0049569]),
(role:TEXT, Examples: [Katrina Ludlow, production mixer, re-recording mixer]),
(result:TEXT, Examples: [Winner, Nominee])
]
# Table: Vote
[
(episode_id:TEXT, Examples: [tt0629204, tt0629228, tt0629170]),
(stars:INTEGER, Examples: [10, 9, 8]),
(votes:INTEGER, Examples: [36, 39, 64]),
(percent:REAL, Examples: [17.7, 19.2, 31.5])
]
# Table: Episode
[
(episode_id:TEXT, Primary Key, Examples: [tt0629146, tt0629149, tt0629153]),
(series:TEXT, Examples: [Law and Order]),
(season:INTEGER, Examples: [9]),
(episode:INTEGER, Examples: [1, 2, 3]),
(number_in_series:INTEGER, Examples: [182, 183, 184]),
(title:TEXT, Examples: [Cherished, DWB, Bait]),
(summary:TEXT),
(air_date:DATE, Examples: [1998-09-23]),
(episode_image:TEXT),
(rating:REAL, Examples: [7.9, 7.6, 8.2]),
(votes:INTEGER, Examples: [203, 177, 159])
]
# Table: Keyword
[
(episode_id:TEXT, Primary Key, Examples: [tt0629239, tt0629397, tt0629420]),
(keyword:TEXT, Primary Key, Examples: [nun, priest, police officer])
]
【Foreign keys】
Credit.episode_id=Episode.episode_id
Credit.person_id=Person.person_id
Award.episode_id=Episode.episode_id
Award.person_id=Person.person_id
Vote.episode_id=Episode.episode_id
Keyword.episode_id=Episode.episode_id

    【Question】
    How many times did the episode titled "Agony" win an award? titled "Agony" refers to title = 'Agony'; win an award refers to result = 'Winner'

    【Evidence】
    titled "Agony" refers to title = 'Agony'; win an award refers to result = 'Winner'

    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.award_id) FROM Episode AS T1 INNER JOIN Award AS T2 ON T1.episode_id = T2.episode_id WHERE T1.title = 'Agony' AND T2.result = 'Winner'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 law_episode
【Schema】
# Table: Credit
[
(episode_id:TEXT, Primary Key, Examples: [tt0629146, tt0629149, tt0629153]),
(person_id:TEXT, Primary Key, Examples: [nm0000973, nm0001583, nm0001832]),
(category:TEXT, Examples: [Additional Crew]),
(role:TEXT, Examples: [technical advisor]),
(credited:TEXT, Examples: [true, false])
]
# Table: Person
[
(person_id:TEXT, Primary Key, Examples: [nm0000210, nm0000973, nm0001346]),
(name:TEXT, Examples: [Julia Roberts, Rene Balcer, Billy Fox]),
(birthdate:DATE, Examples: [1967-10-28]),
(birth_name:TEXT, Examples: [Julia Fiona Roberts]),
(birth_place:TEXT, Examples: [Smyrna, Montreal, Harrisburg]),
(birth_region:TEXT, Examples: [Georgia, Quebec, Pennsylvania]),
(birth_country:TEXT, Examples: [USA, Canada, England]),
(height_meters:REAL, Examples: [1.73, 1.88, 1.93]),
(nickname:TEXT, Examples: [Jules, Gus, Ed])
]
# Table: Award
[
(award_id:INTEGER, Primary Key, Examples: [258, 259, 260]),
(organization:TEXT),
(year:INTEGER, Examples: [1999, 2000]),
(award_category:TEXT, Examples: [Monitor, Primetime Emmy, Silver Gavel Award]),
(award:TEXT),
(series:TEXT, Examples: [Law and Order]),
(episode_id:TEXT, Examples: [tt0629149, tt0629398, tt0629248]),
(person_id:TEXT, Examples: [nm0937725, nm0792309, nm0049569]),
(role:TEXT, Examples: [Katrina Ludlow, production mixer, re-recording mixer]),
(result:TEXT, Examples: [Winner, Nominee])
]
# Table: Vote
[
(episode_id:TEXT, Examples: [tt0629204, tt0629228, tt0629170]),
(stars:INTEGER, Examples: [10, 9, 8]),
(votes:INTEGER, Examples: [36, 39, 64]),
(percent:REAL, Examples: [17.7, 19.2, 31.5])
]
# Table: Episode
[
(episode_id:TEXT, Primary Key, Examples: [tt0629146, tt0629149, tt0629153]),
(series:TEXT, Examples: [Law and Order]),
(season:INTEGER, Examples: [9]),
(episode:INTEGER, Examples: [1, 2, 3]),
(number_in_series:INTEGER, Examples: [182, 183, 184]),
(title:TEXT, Examples: [Cherished, DWB, Bait]),
(summary:TEXT),
(air_date:DATE, Examples: [1998-09-23]),
(episode_image:TEXT),
(rating:REAL, Examples: [7.9, 7.6, 8.2]),
(votes:INTEGER, Examples: [203, 177, 159])
]
# Table: Keyword
[
(episode_id:TEXT, Primary Key, Examples: [tt0629239, tt0629397, tt0629420]),
(keyword:TEXT, Primary Key, Examples: [nun, priest, police officer])
]
【Foreign keys】
Credit.episode_id=Episode.episode_id
Credit.person_id=Person.person_id
Award.episode_id=Episode.episode_id
Award.person_id=Person.person_id
Vote.episode_id=Episode.episode_id
Keyword.episode_id=Episode.episode_id

    【Question】
    How many awards did the "Agony" win? the "Agony" refers to title = 'Agony'; win refers to result = 'Winner'

    【Evidence】
    the "Agony" refers to title = 'Agony'; win refers to result = 'Winner'

    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.award) FROM Episode AS T1 INNER JOIN Award AS T2 ON T1.episode_id = T2.episode_id WHERE T1.title = 'Agony' AND T2.result = 'Winner'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 law_episode
【Schema】
# Table: Credit
[
(episode_id:TEXT, Primary Key, Examples: [tt0629146, tt0629149, tt0629153]),
(person_id:TEXT, Primary Key, Examples: [nm0000973, nm0001583, nm0001832]),
(category:TEXT, Examples: [Additional Crew]),
(role:TEXT, Examples: [technical advisor]),
(credited:TEXT, Examples: [true, false])
]
# Table: Person
[
(person_id:TEXT, Primary Key, Examples: [nm0000210, nm0000973, nm0001346]),
(name:TEXT, Examples: [Julia Roberts, Rene Balcer, Billy Fox]),
(birthdate:DATE, Examples: [1967-10-28]),
(birth_name:TEXT, Examples: [Julia Fiona Roberts]),
(birth_place:TEXT, Examples: [Smyrna, Montreal, Harrisburg]),
(birth_region:TEXT, Examples: [Georgia, Quebec, Pennsylvania]),
(birth_country:TEXT, Examples: [USA, Canada, England]),
(height_meters:REAL, Examples: [1.73, 1.88, 1.93]),
(nickname:TEXT, Examples: [Jules, Gus, Ed])
]
# Table: Award
[
(award_id:INTEGER, Primary Key, Examples: [258, 259, 260]),
(organization:TEXT),
(year:INTEGER, Examples: [1999, 2000]),
(award_category:TEXT, Examples: [Monitor, Primetime Emmy, Silver Gavel Award]),
(award:TEXT),
(series:TEXT, Examples: [Law and Order]),
(episode_id:TEXT, Examples: [tt0629149, tt0629398, tt0629248]),
(person_id:TEXT, Examples: [nm0937725, nm0792309, nm0049569]),
(role:TEXT, Examples: [Katrina Ludlow, production mixer, re-recording mixer]),
(result:TEXT, Examples: [Winner, Nominee])
]
# Table: Vote
[
(episode_id:TEXT, Examples: [tt0629204, tt0629228, tt0629170]),
(stars:INTEGER, Examples: [10, 9, 8]),
(votes:INTEGER, Examples: [36, 39, 64]),
(percent:REAL, Examples: [17.7, 19.2, 31.5])
]
# Table: Episode
[
(episode_id:TEXT, Primary Key, Examples: [tt0629146, tt0629149, tt0629153]),
(series:TEXT, Examples: [Law and Order]),
(season:INTEGER, Examples: [9]),
(episode:INTEGER, Examples: [1, 2, 3]),
(number_in_series:INTEGER, Examples: [182, 183, 184]),
(title:TEXT, Examples: [Cherished, DWB, Bait]),
(summary:TEXT),
(air_date:DATE, Examples: [1998-09-23]),
(episode_image:TEXT),
(rating:REAL, Examples: [7.9, 7.6, 8.2]),
(votes:INTEGER, Examples: [203, 177, 159])
]
# Table: Keyword
[
(episode_id:TEXT, Primary Key, Examples: [tt0629239, tt0629397, tt0629420]),
(keyword:TEXT, Primary Key, Examples: [nun, priest, police officer])
]
【Foreign keys】
Credit.episode_id=Episode.episode_id
Credit.person_id=Person.person_id
Award.episode_id=Episode.episode_id
Award.person_id=Person.person_id
Vote.episode_id=Episode.episode_id
Keyword.episode_id=Episode.episode_id

    【Question】
    Who is the stunt coordinator in episode 3? who refers to name; stunt coordinator refers to role = 'stunt coordinator'

    【Evidence】
    who refers to name; stunt coordinator refers to role = 'stunt coordinator'

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

SQL: SELECT T3.name FROM Episode AS T1 INNER JOIN Credit AS T2 ON T1.episode_id = T2.episode_id INNER JOIN Person AS T3 ON T3.person_id = T2.person_id WHERE T1.episode = 3 AND T2.role = 'stunt coordinator'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 law_episode
【Schema】
# Table: Credit
[
(episode_id:TEXT, Primary Key, Examples: [tt0629146, tt0629149, tt0629153]),
(person_id:TEXT, Primary Key, Examples: [nm0000973, nm0001583, nm0001832]),
(category:TEXT, Examples: [Additional Crew]),
(role:TEXT, Examples: [technical advisor]),
(credited:TEXT, Examples: [true, false])
]
# Table: Person
[
(person_id:TEXT, Primary Key, Examples: [nm0000210, nm0000973, nm0001346]),
(name:TEXT, Examples: [Julia Roberts, Rene Balcer, Billy Fox]),
(birthdate:DATE, Examples: [1967-10-28]),
(birth_name:TEXT, Examples: [Julia Fiona Roberts]),
(birth_place:TEXT, Examples: [Smyrna, Montreal, Harrisburg]),
(birth_region:TEXT, Examples: [Georgia, Quebec, Pennsylvania]),
(birth_country:TEXT, Examples: [USA, Canada, England]),
(height_meters:REAL, Examples: [1.73, 1.88, 1.93]),
(nickname:TEXT, Examples: [Jules, Gus, Ed])
]
# Table: Award
[
(award_id:INTEGER, Primary Key, Examples: [258, 259, 260]),
(organization:TEXT),
(year:INTEGER, Examples: [1999, 2000]),
(award_category:TEXT, Examples: [Monitor, Primetime Emmy, Silver Gavel Award]),
(award:TEXT),
(series:TEXT, Examples: [Law and Order]),
(episode_id:TEXT, Examples: [tt0629149, tt0629398, tt0629248]),
(person_id:TEXT, Examples: [nm0937725, nm0792309, nm0049569]),
(role:TEXT, Examples: [Katrina Ludlow, production mixer, re-recording mixer]),
(result:TEXT, Examples: [Winner, Nominee])
]
# Table: Vote
[
(episode_id:TEXT, Examples: [tt0629204, tt0629228, tt0629170]),
(stars:INTEGER, Examples: [10, 9, 8]),
(votes:INTEGER, Examples: [36, 39, 64]),
(percent:REAL, Examples: [17.7, 19.2, 31.5])
]
# Table: Episode
[
(episode_id:TEXT, Primary Key, Examples: [tt0629146, tt0629149, tt0629153]),
(series:TEXT, Examples: [Law and Order]),
(season:INTEGER, Examples: [9]),
(episode:INTEGER, Examples: [1, 2, 3]),
(number_in_series:INTEGER, Examples: [182, 183, 184]),
(title:TEXT, Examples: [Cherished, DWB, Bait]),
(summary:TEXT),
(air_date:DATE, Examples: [1998-09-23]),
(episode_image:TEXT),
(rating:REAL, Examples: [7.9, 7.6, 8.2]),
(votes:INTEGER, Examples: [203, 177, 159])
]
# Table: Keyword
[
(episode_id:TEXT, Primary Key, Examples: [tt0629239, tt0629397, tt0629420]),
(keyword:TEXT, Primary Key, Examples: [nun, priest, police officer])
]
【Foreign keys】
Credit.episode_id=Episode.episode_id
Credit.person_id=Person.person_id
Award.episode_id=Episode.episode_id
Award.person_id=Person.person_id
Vote.episode_id=Episode.episode_id
Keyword.episode_id=Episode.episode_id

    【Question】
    How many people were not credited at the end of the "Admissions" episode? not credited refers to credited = ''; the "Admissions" episode refers to title = 'Admissions'

    【Evidence】
    not credited refers to credited = ''; the "Admissions" episode refers to title = 'Admissions'

    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.person_id) FROM Episode AS T1 INNER JOIN Credit AS T2 ON T1.episode_id = T2.episode_id WHERE T1.title = 'Admissions' AND T2.credited = 'false'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 law_episode
【Schema】
# Table: Credit
[
(episode_id:TEXT, Primary Key, Examples: [tt0629146, tt0629149, tt0629153]),
(person_id:TEXT, Primary Key, Examples: [nm0000973, nm0001583, nm0001832]),
(category:TEXT, Examples: [Additional Crew]),
(role:TEXT, Examples: [technical advisor]),
(credited:TEXT, Examples: [true, false])
]
# Table: Person
[
(person_id:TEXT, Primary Key, Examples: [nm0000210, nm0000973, nm0001346]),
(name:TEXT, Examples: [Julia Roberts, Rene Balcer, Billy Fox]),
(birthdate:DATE, Examples: [1967-10-28]),
(birth_name:TEXT, Examples: [Julia Fiona Roberts]),
(birth_place:TEXT, Examples: [Smyrna, Montreal, Harrisburg]),
(birth_region:TEXT, Examples: [Georgia, Quebec, Pennsylvania]),
(birth_country:TEXT, Examples: [USA, Canada, England]),
(height_meters:REAL, Examples: [1.73, 1.88, 1.93]),
(nickname:TEXT, Examples: [Jules, Gus, Ed])
]
# Table: Award
[
(award_id:INTEGER, Primary Key, Examples: [258, 259, 260]),
(organization:TEXT),
(year:INTEGER, Examples: [1999, 2000]),
(award_category:TEXT, Examples: [Monitor, Primetime Emmy, Silver Gavel Award]),
(award:TEXT),
(series:TEXT, Examples: [Law and Order]),
(episode_id:TEXT, Examples: [tt0629149, tt0629398, tt0629248]),
(person_id:TEXT, Examples: [nm0937725, nm0792309, nm0049569]),
(role:TEXT, Examples: [Katrina Ludlow, production mixer, re-recording mixer]),
(result:TEXT, Examples: [Winner, Nominee])
]
# Table: Vote
[
(episode_id:TEXT, Examples: [tt0629204, tt0629228, tt0629170]),
(stars:INTEGER, Examples: [10, 9, 8]),
(votes:INTEGER, Examples: [36, 39, 64]),
(percent:REAL, Examples: [17.7, 19.2, 31.5])
]
# Table: Episode
[
(episode_id:TEXT, Primary Key, Examples: [tt0629146, tt0629149, tt0629153]),
(series:TEXT, Examples: [Law and Order]),
(season:INTEGER, Examples: [9]),
(episode:INTEGER, Examples: [1, 2, 3]),
(number_in_series:INTEGER, Examples: [182, 183, 184]),
(title:TEXT, Examples: [Cherished, DWB, Bait]),
(summary:TEXT),
(air_date:DATE, Examples: [1998-09-23]),
(episode_image:TEXT),
(rating:REAL, Examples: [7.9, 7.6, 8.2]),
(votes:INTEGER, Examples: [203, 177, 159])
]
# Table: Keyword
[
(episode_id:TEXT, Primary Key, Examples: [tt0629239, tt0629397, tt0629420]),
(keyword:TEXT, Primary Key, Examples: [nun, priest, police officer])
]
【Foreign keys】
Credit.episode_id=Episode.episode_id
Credit.person_id=Person.person_id
Award.episode_id=Episode.episode_id
Award.person_id=Person.person_id
Vote.episode_id=Episode.episode_id
Keyword.episode_id=Episode.episode_id

    【Question】
    How many roles did Julia Roberts play in the series?

    【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(T1.role) FROM Credit AS T1 INNER JOIN Person AS T2 ON T2.person_id = T1.person_id WHERE T2.name = 'Julia Roberts'