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】 university
【Schema】
# Table: university_year
[
(university_id:INTEGER, Examples: [1, 5, 2]),
(year:INTEGER, Examples: [2011, 2012, 2013]),
(num_students:INTEGER, Examples: [20152, 2243, 11074]),
(student_staff_ratio:REAL, Examples: [8.9, 6.9, 9.0]),
(pct_international_students:INTEGER, Examples: [25, 27, 33]),
(pct_female_students:INTEGER, Examples: [33, 37, 42])
]
# Table: country
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country_name:TEXT, Examples: [Argentina, Australia, Austria])
]
# Table: university
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country_id:INTEGER, Examples: [73, 72, 33]),
(university_name:TEXT, Examples: [Harvard University])
]
# Table: university_ranking_year
[
(university_id:INTEGER, Examples: [1, 5, 2]),
(ranking_criteria_id:INTEGER, Examples: [1, 2, 3]),
(year:INTEGER, Examples: [2011, 2012, 2013]),
(score:INTEGER, Examples: [100, 98, 91])
]
# Table: ranking_system
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(system_name:TEXT, Examples: [Times Higher Education World University Ranking])
]
# Table: ranking_criteria
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(ranking_system_id:INTEGER, Examples: [1, 2, 3]),
(criteria_name:TEXT, Examples: [Teaching, International, Research])
]
【Foreign keys】
university_year.university_id=university.id
university.country_id=country.id
university_ranking_year.ranking_criteria_id=ranking_criteria.id
university_ranking_year.university_id=university.id
ranking_criteria.ranking_system_id=ranking_system.id

    【Question】
    In which country does the most populated university in 2014 located ? the most populated university refers to max(num_students); in 2014 refers to year = 2014

    【Evidence】
    the most populated university refers to max(num_students); in 2014 refers to year = 2014

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

SQL: SELECT T2.country_id FROM university_year AS T1 INNER JOIN university AS T2 ON T1.university_id = T2.id WHERE T1.year = 2014 ORDER BY T1.num_students DESC LIMIT 1
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 university
【Schema】
# Table: university_year
[
(university_id:INTEGER, Examples: [1, 5, 2]),
(year:INTEGER, Examples: [2011, 2012, 2013]),
(num_students:INTEGER, Examples: [20152, 2243, 11074]),
(student_staff_ratio:REAL, Examples: [8.9, 6.9, 9.0]),
(pct_international_students:INTEGER, Examples: [25, 27, 33]),
(pct_female_students:INTEGER, Examples: [33, 37, 42])
]
# Table: country
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country_name:TEXT, Examples: [Argentina, Australia, Austria])
]
# Table: university
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country_id:INTEGER, Examples: [73, 72, 33]),
(university_name:TEXT, Examples: [Harvard University])
]
# Table: university_ranking_year
[
(university_id:INTEGER, Examples: [1, 5, 2]),
(ranking_criteria_id:INTEGER, Examples: [1, 2, 3]),
(year:INTEGER, Examples: [2011, 2012, 2013]),
(score:INTEGER, Examples: [100, 98, 91])
]
# Table: ranking_system
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(system_name:TEXT, Examples: [Times Higher Education World University Ranking])
]
# Table: ranking_criteria
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(ranking_system_id:INTEGER, Examples: [1, 2, 3]),
(criteria_name:TEXT, Examples: [Teaching, International, Research])
]
【Foreign keys】
university_year.university_id=university.id
university.country_id=country.id
university_ranking_year.ranking_criteria_id=ranking_criteria.id
university_ranking_year.university_id=university.id
ranking_criteria.ranking_system_id=ranking_system.id

    【Question】
    Give the score and number of international students in university ID 100 in 2015. number of international students refers to DIVIDE(MULTIPLY(num_students, pct_international_students), 100); in 2015 refers to year = 2015

    【Evidence】
    number of international students refers to DIVIDE(MULTIPLY(num_students, pct_international_students), 100); in 2015 refers to year = 2015

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

SQL: SELECT CAST(T1.num_students * T1.pct_international_students AS REAL) / 100, T2.score FROM university_year AS T1 INNER JOIN university_ranking_year AS T2 ON T1.university_id = T2.university_id WHERE T2.year = 2015 AND T1.university_id = 100
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 university
【Schema】
# Table: university_year
[
(university_id:INTEGER, Examples: [1, 5, 2]),
(year:INTEGER, Examples: [2011, 2012, 2013]),
(num_students:INTEGER, Examples: [20152, 2243, 11074]),
(student_staff_ratio:REAL, Examples: [8.9, 6.9, 9.0]),
(pct_international_students:INTEGER, Examples: [25, 27, 33]),
(pct_female_students:INTEGER, Examples: [33, 37, 42])
]
# Table: country
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country_name:TEXT, Examples: [Argentina, Australia, Austria])
]
# Table: university
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country_id:INTEGER, Examples: [73, 72, 33]),
(university_name:TEXT, Examples: [Harvard University])
]
# Table: university_ranking_year
[
(university_id:INTEGER, Examples: [1, 5, 2]),
(ranking_criteria_id:INTEGER, Examples: [1, 2, 3]),
(year:INTEGER, Examples: [2011, 2012, 2013]),
(score:INTEGER, Examples: [100, 98, 91])
]
# Table: ranking_system
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(system_name:TEXT, Examples: [Times Higher Education World University Ranking])
]
# Table: ranking_criteria
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(ranking_system_id:INTEGER, Examples: [1, 2, 3]),
(criteria_name:TEXT, Examples: [Teaching, International, Research])
]
【Foreign keys】
university_year.university_id=university.id
university.country_id=country.id
university_ranking_year.ranking_criteria_id=ranking_criteria.id
university_ranking_year.university_id=university.id
ranking_criteria.ranking_system_id=ranking_system.id

    【Question】
    What is the student population of the university that scored 98 in 2013? student population refers to num_students; in 2013 refers to year = 2013

    【Evidence】
    student population refers to num_students; in 2013 refers to year = 2013

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

SQL: SELECT SUM(T1.num_students) FROM university_year AS T1 INNER JOIN university_ranking_year AS T2 ON T1.university_id = T2.university_id WHERE T2.score = 98 AND T1.year = 2013
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 university
【Schema】
# Table: university_year
[
(university_id:INTEGER, Examples: [1, 5, 2]),
(year:INTEGER, Examples: [2011, 2012, 2013]),
(num_students:INTEGER, Examples: [20152, 2243, 11074]),
(student_staff_ratio:REAL, Examples: [8.9, 6.9, 9.0]),
(pct_international_students:INTEGER, Examples: [25, 27, 33]),
(pct_female_students:INTEGER, Examples: [33, 37, 42])
]
# Table: country
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country_name:TEXT, Examples: [Argentina, Australia, Austria])
]
# Table: university
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country_id:INTEGER, Examples: [73, 72, 33]),
(university_name:TEXT, Examples: [Harvard University])
]
# Table: university_ranking_year
[
(university_id:INTEGER, Examples: [1, 5, 2]),
(ranking_criteria_id:INTEGER, Examples: [1, 2, 3]),
(year:INTEGER, Examples: [2011, 2012, 2013]),
(score:INTEGER, Examples: [100, 98, 91])
]
# Table: ranking_system
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(system_name:TEXT, Examples: [Times Higher Education World University Ranking])
]
# Table: ranking_criteria
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(ranking_system_id:INTEGER, Examples: [1, 2, 3]),
(criteria_name:TEXT, Examples: [Teaching, International, Research])
]
【Foreign keys】
university_year.university_id=university.id
university.country_id=country.id
university_ranking_year.ranking_criteria_id=ranking_criteria.id
university_ranking_year.university_id=university.id
ranking_criteria.ranking_system_id=ranking_system.id

    【Question】
    List the criteria names under the ranking system called Center for World University Ranking. ranking system called Center for World University Ranking refers to system_name = 'Center for World University Rankings';

    【Evidence】
    ranking system called Center for World University Ranking refers to system_name = 'Center for World University Rankings';

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

SQL: SELECT T2.criteria_name FROM ranking_system AS T1 INNER JOIN ranking_criteria AS T2 ON T1.id = T2.ranking_system_id WHERE T1.system_name = 'Center for World University Rankings'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 university
【Schema】
# Table: university_year
[
(university_id:INTEGER, Examples: [1, 5, 2]),
(year:INTEGER, Examples: [2011, 2012, 2013]),
(num_students:INTEGER, Examples: [20152, 2243, 11074]),
(student_staff_ratio:REAL, Examples: [8.9, 6.9, 9.0]),
(pct_international_students:INTEGER, Examples: [25, 27, 33]),
(pct_female_students:INTEGER, Examples: [33, 37, 42])
]
# Table: country
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country_name:TEXT, Examples: [Argentina, Australia, Austria])
]
# Table: university
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country_id:INTEGER, Examples: [73, 72, 33]),
(university_name:TEXT, Examples: [Harvard University])
]
# Table: university_ranking_year
[
(university_id:INTEGER, Examples: [1, 5, 2]),
(ranking_criteria_id:INTEGER, Examples: [1, 2, 3]),
(year:INTEGER, Examples: [2011, 2012, 2013]),
(score:INTEGER, Examples: [100, 98, 91])
]
# Table: ranking_system
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(system_name:TEXT, Examples: [Times Higher Education World University Ranking])
]
# Table: ranking_criteria
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(ranking_system_id:INTEGER, Examples: [1, 2, 3]),
(criteria_name:TEXT, Examples: [Teaching, International, Research])
]
【Foreign keys】
university_year.university_id=university.id
university.country_id=country.id
university_ranking_year.ranking_criteria_id=ranking_criteria.id
university_ranking_year.university_id=university.id
ranking_criteria.ranking_system_id=ranking_system.id

    【Question】
    Provide the country name of universities with the number of students greater than 98% of the average student population of all universities in 2013. number of students greater than 98% of the average student population of all universities refers to num_students >  MULTPLY(num_students, 0.98); in 2013 refers to year = 2013

    【Evidence】
    number of students greater than 98% of the average student population of all universities refers to num_students >  MULTPLY(num_students, 0.98); in 2013 refers to year = 2013

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

SQL: SELECT DISTINCT T3.country_name FROM university AS T1 INNER JOIN university_year AS T2 ON T1.id = T2.university_id INNER JOIN country AS T3 ON T3.id = T1.country_id WHERE T2.year = 2013 AND T2.num_students * 100 > ( SELECT AVG(num_students) FROM university_year ) * 98
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 university
【Schema】
# Table: university_year
[
(university_id:INTEGER, Examples: [1, 5, 2]),
(year:INTEGER, Examples: [2011, 2012, 2013]),
(num_students:INTEGER, Examples: [20152, 2243, 11074]),
(student_staff_ratio:REAL, Examples: [8.9, 6.9, 9.0]),
(pct_international_students:INTEGER, Examples: [25, 27, 33]),
(pct_female_students:INTEGER, Examples: [33, 37, 42])
]
# Table: country
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country_name:TEXT, Examples: [Argentina, Australia, Austria])
]
# Table: university
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country_id:INTEGER, Examples: [73, 72, 33]),
(university_name:TEXT, Examples: [Harvard University])
]
# Table: university_ranking_year
[
(university_id:INTEGER, Examples: [1, 5, 2]),
(ranking_criteria_id:INTEGER, Examples: [1, 2, 3]),
(year:INTEGER, Examples: [2011, 2012, 2013]),
(score:INTEGER, Examples: [100, 98, 91])
]
# Table: ranking_system
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(system_name:TEXT, Examples: [Times Higher Education World University Ranking])
]
# Table: ranking_criteria
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(ranking_system_id:INTEGER, Examples: [1, 2, 3]),
(criteria_name:TEXT, Examples: [Teaching, International, Research])
]
【Foreign keys】
university_year.university_id=university.id
university.country_id=country.id
university_ranking_year.ranking_criteria_id=ranking_criteria.id
university_ranking_year.university_id=university.id
ranking_criteria.ranking_system_id=ranking_system.id

    【Question】
    Among universities that score below 80 in 2015, what is the percentage of international students? score below 80 refers to score < 80; in 2015 refers to year 2015; percentage of international students refers to DIVIDE(SUM(DIVIDE(MULTIPLY(num_students, pct_international_students), 100)), SUM(num_students))

    【Evidence】
    score below 80 refers to score < 80; in 2015 refers to year 2015; percentage of international students refers to DIVIDE(SUM(DIVIDE(MULTIPLY(num_students, pct_international_students), 100)), SUM(num_students))

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

SQL: SELECT SUM(CAST(T1.num_students * T1.pct_international_students AS REAL) / 100) / COUNT(*) * 100 FROM university_year AS T1 INNER JOIN university_ranking_year AS T2 ON T1.university_id = T2.university_id WHERE T2.score < 80 AND T1.year = 2015
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 university
【Schema】
# Table: university_year
[
(university_id:INTEGER, Examples: [1, 5, 2]),
(year:INTEGER, Examples: [2011, 2012, 2013]),
(num_students:INTEGER, Examples: [20152, 2243, 11074]),
(student_staff_ratio:REAL, Examples: [8.9, 6.9, 9.0]),
(pct_international_students:INTEGER, Examples: [25, 27, 33]),
(pct_female_students:INTEGER, Examples: [33, 37, 42])
]
# Table: country
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country_name:TEXT, Examples: [Argentina, Australia, Austria])
]
# Table: university
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country_id:INTEGER, Examples: [73, 72, 33]),
(university_name:TEXT, Examples: [Harvard University])
]
# Table: university_ranking_year
[
(university_id:INTEGER, Examples: [1, 5, 2]),
(ranking_criteria_id:INTEGER, Examples: [1, 2, 3]),
(year:INTEGER, Examples: [2011, 2012, 2013]),
(score:INTEGER, Examples: [100, 98, 91])
]
# Table: ranking_system
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(system_name:TEXT, Examples: [Times Higher Education World University Ranking])
]
# Table: ranking_criteria
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(ranking_system_id:INTEGER, Examples: [1, 2, 3]),
(criteria_name:TEXT, Examples: [Teaching, International, Research])
]
【Foreign keys】
university_year.university_id=university.id
university.country_id=country.id
university_ranking_year.ranking_criteria_id=ranking_criteria.id
university_ranking_year.university_id=university.id
ranking_criteria.ranking_system_id=ranking_system.id

    【Question】
    How many students attended universities were there in 2011? in 2011 refers to year = 2011;

    【Evidence】
    in 2011 refers to year = 2011;

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

SQL: SELECT SUM(num_students) FROM university_year WHERE year = 2011
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 university
【Schema】
# Table: university_year
[
(university_id:INTEGER, Examples: [1, 5, 2]),
(year:INTEGER, Examples: [2011, 2012, 2013]),
(num_students:INTEGER, Examples: [20152, 2243, 11074]),
(student_staff_ratio:REAL, Examples: [8.9, 6.9, 9.0]),
(pct_international_students:INTEGER, Examples: [25, 27, 33]),
(pct_female_students:INTEGER, Examples: [33, 37, 42])
]
# Table: country
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country_name:TEXT, Examples: [Argentina, Australia, Austria])
]
# Table: university
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country_id:INTEGER, Examples: [73, 72, 33]),
(university_name:TEXT, Examples: [Harvard University])
]
# Table: university_ranking_year
[
(university_id:INTEGER, Examples: [1, 5, 2]),
(ranking_criteria_id:INTEGER, Examples: [1, 2, 3]),
(year:INTEGER, Examples: [2011, 2012, 2013]),
(score:INTEGER, Examples: [100, 98, 91])
]
# Table: ranking_system
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(system_name:TEXT, Examples: [Times Higher Education World University Ranking])
]
# Table: ranking_criteria
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(ranking_system_id:INTEGER, Examples: [1, 2, 3]),
(criteria_name:TEXT, Examples: [Teaching, International, Research])
]
【Foreign keys】
university_year.university_id=university.id
university.country_id=country.id
university_ranking_year.ranking_criteria_id=ranking_criteria.id
university_ranking_year.university_id=university.id
ranking_criteria.ranking_system_id=ranking_system.id

    【Question】
    Among all universities, how many female students were there in 2011? in 2011 refers to year = 2011; female students refers to SUM(DIVIDE(MULTIPLY(num_students, pct_female_students), 100))

    【Evidence】
    in 2011 refers to year = 2011; female students refers to SUM(DIVIDE(MULTIPLY(num_students, pct_female_students), 100))

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

SQL: SELECT SUM(CAST(num_students * pct_female_students AS REAL) / 100) FROM university_year WHERE year = 2011
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 university
【Schema】
# Table: university_year
[
(university_id:INTEGER, Examples: [1, 5, 2]),
(year:INTEGER, Examples: [2011, 2012, 2013]),
(num_students:INTEGER, Examples: [20152, 2243, 11074]),
(student_staff_ratio:REAL, Examples: [8.9, 6.9, 9.0]),
(pct_international_students:INTEGER, Examples: [25, 27, 33]),
(pct_female_students:INTEGER, Examples: [33, 37, 42])
]
# Table: country
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country_name:TEXT, Examples: [Argentina, Australia, Austria])
]
# Table: university
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country_id:INTEGER, Examples: [73, 72, 33]),
(university_name:TEXT, Examples: [Harvard University])
]
# Table: university_ranking_year
[
(university_id:INTEGER, Examples: [1, 5, 2]),
(ranking_criteria_id:INTEGER, Examples: [1, 2, 3]),
(year:INTEGER, Examples: [2011, 2012, 2013]),
(score:INTEGER, Examples: [100, 98, 91])
]
# Table: ranking_system
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(system_name:TEXT, Examples: [Times Higher Education World University Ranking])
]
# Table: ranking_criteria
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(ranking_system_id:INTEGER, Examples: [1, 2, 3]),
(criteria_name:TEXT, Examples: [Teaching, International, Research])
]
【Foreign keys】
university_year.university_id=university.id
university.country_id=country.id
university_ranking_year.ranking_criteria_id=ranking_criteria.id
university_ranking_year.university_id=university.id
ranking_criteria.ranking_system_id=ranking_system.id

    【Question】
    What is the student staff ratio at the university with the greatest student staff ratio of all time? greatest student staff ratio of all time refers to max(student_staff_ratio)

    【Evidence】
    greatest student staff ratio of all time refers to max(student_staff_ratio)

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

SQL: SELECT MAX(student_staff_ratio) FROM university_year ORDER BY student_staff_ratio DESC LIMIT 1
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 university
【Schema】
# Table: university_year
[
(university_id:INTEGER, Examples: [1, 5, 2]),
(year:INTEGER, Examples: [2011, 2012, 2013]),
(num_students:INTEGER, Examples: [20152, 2243, 11074]),
(student_staff_ratio:REAL, Examples: [8.9, 6.9, 9.0]),
(pct_international_students:INTEGER, Examples: [25, 27, 33]),
(pct_female_students:INTEGER, Examples: [33, 37, 42])
]
# Table: country
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country_name:TEXT, Examples: [Argentina, Australia, Austria])
]
# Table: university
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country_id:INTEGER, Examples: [73, 72, 33]),
(university_name:TEXT, Examples: [Harvard University])
]
# Table: university_ranking_year
[
(university_id:INTEGER, Examples: [1, 5, 2]),
(ranking_criteria_id:INTEGER, Examples: [1, 2, 3]),
(year:INTEGER, Examples: [2011, 2012, 2013]),
(score:INTEGER, Examples: [100, 98, 91])
]
# Table: ranking_system
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(system_name:TEXT, Examples: [Times Higher Education World University Ranking])
]
# Table: ranking_criteria
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(ranking_system_id:INTEGER, Examples: [1, 2, 3]),
(criteria_name:TEXT, Examples: [Teaching, International, Research])
]
【Foreign keys】
university_year.university_id=university.id
university.country_id=country.id
university_ranking_year.ranking_criteria_id=ranking_criteria.id
university_ranking_year.university_id=university.id
ranking_criteria.ranking_system_id=ranking_system.id

    【Question】
    What is the university ID with the most students in 2011? most students refers to MAX(num_students), in 2011 refers to year = 2011

    【Evidence】
    most students refers to MAX(num_students), in 2011 refers to year = 2011

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

SQL: SELECT university_id FROM university_year WHERE year = 2011 ORDER BY num_students DESC LIMIT 1