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】 shooting
【Schema】
# Table: officers
[
(case_number:TEXT, Examples: [44523A, 121982X, 605484T]),
(race:TEXT, Examples: [L, W, B]),
(gender:TEXT, Examples: [M, F]),
(last_name:TEXT, Examples: [Patino, Fillingim, Padilla]),
(first_name:TEXT, Examples: [Michael, Brian, Gilbert]),
(full_name:TEXT, Examples: [Patino, Michael, Fillingim, Brian, Padilla, Gilbert])
]
# Table: incidents
[
(case_number:TEXT, Primary Key, Examples: [031347-2015, 072458-2016, 089985-2016]),
(date:DATE),
(location:TEXT, Examples: [7400 Bonnie View Road]),
(subject_statuses:TEXT, Examples: [Deceased, Shoot and Miss, Injured]),
(subject_weapon:TEXT, Examples: [Vehicle, Shotgun, Handgun]),
(subjects:TEXT, Examples: [Luster, Desmond Dwayne B/M]),
(subject_count:INTEGER, Examples: [1, 2, 0]),
(officers:TEXT, Examples: [Tollerton, Aaron W/M, Cardenas, Steven L/M, Ruben, Fredirick W/M])
]
# Table: subjects
[
(case_number:TEXT, Examples: [44523A, 121982X, 605484T]),
(race:TEXT, Examples: [L, B, W]),
(gender:TEXT, Examples: [M, F]),
(last_name:TEXT, Examples: [Curry, Chavez, Salinas]),
(first_name:TEXT, Examples: [James, Gabriel, Nick]),
(full_name:TEXT, Examples: [Curry, James, Chavez, Gabriel, Salinas, Nick])
]
【Foreign keys】
officers.case_number=incidents.case_number
subjects.case_number=incidents.case_number

    【Question】
    Which type of weapon was used to attack the victim in the record number 031347-2015? What is the victim's race and gender? type of weapon refers to subject_weapon; record number 031347-2015 refers to case_number = '031347-2015'

    【Evidence】
    type of weapon refers to subject_weapon; record number 031347-2015 refers to case_number = '031347-2015'

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

SQL: SELECT T1.subject_weapon, T2.race, T2.gender FROM incidents AS T1 INNER JOIN subjects AS T2 ON T1.case_number = T2.case_number WHERE T1.case_number = '031347-2015'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 shooting
【Schema】
# Table: officers
[
(case_number:TEXT, Examples: [44523A, 121982X, 605484T]),
(race:TEXT, Examples: [L, W, B]),
(gender:TEXT, Examples: [M, F]),
(last_name:TEXT, Examples: [Patino, Fillingim, Padilla]),
(first_name:TEXT, Examples: [Michael, Brian, Gilbert]),
(full_name:TEXT, Examples: [Patino, Michael, Fillingim, Brian, Padilla, Gilbert])
]
# Table: incidents
[
(case_number:TEXT, Primary Key, Examples: [031347-2015, 072458-2016, 089985-2016]),
(date:DATE),
(location:TEXT, Examples: [7400 Bonnie View Road]),
(subject_statuses:TEXT, Examples: [Deceased, Shoot and Miss, Injured]),
(subject_weapon:TEXT, Examples: [Vehicle, Shotgun, Handgun]),
(subjects:TEXT, Examples: [Luster, Desmond Dwayne B/M]),
(subject_count:INTEGER, Examples: [1, 2, 0]),
(officers:TEXT, Examples: [Tollerton, Aaron W/M, Cardenas, Steven L/M, Ruben, Fredirick W/M])
]
# Table: subjects
[
(case_number:TEXT, Examples: [44523A, 121982X, 605484T]),
(race:TEXT, Examples: [L, B, W]),
(gender:TEXT, Examples: [M, F]),
(last_name:TEXT, Examples: [Curry, Chavez, Salinas]),
(first_name:TEXT, Examples: [James, Gabriel, Nick]),
(full_name:TEXT, Examples: [Curry, James, Chavez, Gabriel, Salinas, Nick])
]
【Foreign keys】
officers.case_number=incidents.case_number
subjects.case_number=incidents.case_number

    【Question】
    Which near-death incident did a policeman by the name of Ruben Fredirick look into? What is the victim in this incident's race and gender? near-death refers to subject_statuses = 'Deceased Injured'; incident refers to case_number; Ruben Fredirick refers to full_name = 'Ruben Fredirick'

    【Evidence】
    near-death refers to subject_statuses = 'Deceased Injured'; incident refers to case_number; Ruben Fredirick refers to full_name = 'Ruben Fredirick'

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

SQL: SELECT T1.case_number, T3.race, T3.gender FROM incidents AS T1 INNER JOIN officers AS T2 ON T1.case_number = T2.case_number INNER JOIN subjects AS T3 ON T1.case_number = T3.case_number WHERE T2.first_name = 'Fredirick' AND T2.last_name = 'Ruben'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 shooting
【Schema】
# Table: officers
[
(case_number:TEXT, Examples: [44523A, 121982X, 605484T]),
(race:TEXT, Examples: [L, W, B]),
(gender:TEXT, Examples: [M, F]),
(last_name:TEXT, Examples: [Patino, Fillingim, Padilla]),
(first_name:TEXT, Examples: [Michael, Brian, Gilbert]),
(full_name:TEXT, Examples: [Patino, Michael, Fillingim, Brian, Padilla, Gilbert])
]
# Table: incidents
[
(case_number:TEXT, Primary Key, Examples: [031347-2015, 072458-2016, 089985-2016]),
(date:DATE),
(location:TEXT, Examples: [7400 Bonnie View Road]),
(subject_statuses:TEXT, Examples: [Deceased, Shoot and Miss, Injured]),
(subject_weapon:TEXT, Examples: [Vehicle, Shotgun, Handgun]),
(subjects:TEXT, Examples: [Luster, Desmond Dwayne B/M]),
(subject_count:INTEGER, Examples: [1, 2, 0]),
(officers:TEXT, Examples: [Tollerton, Aaron W/M, Cardenas, Steven L/M, Ruben, Fredirick W/M])
]
# Table: subjects
[
(case_number:TEXT, Examples: [44523A, 121982X, 605484T]),
(race:TEXT, Examples: [L, B, W]),
(gender:TEXT, Examples: [M, F]),
(last_name:TEXT, Examples: [Curry, Chavez, Salinas]),
(first_name:TEXT, Examples: [James, Gabriel, Nick]),
(full_name:TEXT, Examples: [Curry, James, Chavez, Gabriel, Salinas, Nick])
]
【Foreign keys】
officers.case_number=incidents.case_number
subjects.case_number=incidents.case_number

    【Question】
    What proportion of male police officers looked into events where people were injured? male refers to gender = 'M'; people were injured refers to subject_statuses = 'Injured'; proportion = divide(count(case_number where gender = 'M'), count(case_number)) where subject_statuses = 'Injured' * 100%

    【Evidence】
    male refers to gender = 'M'; people were injured refers to subject_statuses = 'Injured'; proportion = divide(count(case_number where gender = 'M'), count(case_number)) where subject_statuses = 'Injured' * 100%

    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(T2.gender = 'M') AS REAL) * 100 / COUNT(T1.case_number) FROM incidents T1 INNER JOIN officers T2 ON T1.case_number = T2.case_number WHERE T1.subject_statuses = 'Injured'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 genes
【Schema】
# Table: Interactions
[
(GeneID1:TEXT, Primary Key, Examples: [G234064, G234065, G234073]),
(GeneID2:TEXT, Primary Key, Examples: [G234126, G235065, G234371]),
(Type:TEXT, Examples: [Genetic-Physical, Genetic, Physical]),
(Expression_Corr:REAL, Examples: [0.914095071, 0.751584888, 0.823773738])
]
# Table: Classification
[
(GeneID:TEXT, Primary Key, Examples: [G234064, G234065, G234070]),
(Localization:TEXT, Examples: [cytoplasm, cytoskeleton, nucleus])
]
# Table: Genes
[
(GeneID:TEXT, Examples: [G234064, G234065, G234070]),
(Essential:TEXT, Examples: [Essential, Non-Essential, ?]),
(Class:TEXT, Examples: [GTP/GDP-exchange factors (GEFs)]),
(Complex:TEXT, Examples: [Translation complexes]),
(Phenotype:TEXT, Examples: [?]),
(Motif:TEXT, Examples: [PS00824, PS00825, ?]),
(Chromosome:INTEGER, Examples: [1, 2, 3]),
(Function:TEXT),
(Localization:TEXT, Examples: [cytoplasm, cytoskeleton, nucleus])
]
【Foreign keys】
Interactions.GeneID1=Classification.GeneID
Interactions.GeneID2=Classification.GeneID
Genes.GeneID=Classification.GeneID

    【Question】
    For the genes that are located in the plasma membrane, please list their number of chromosomes.

    【Evidence】
    

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

SQL: SELECT T1.Chromosome FROM Genes AS T1 INNER JOIN Classification AS T2 ON T1.GeneID = T2.GeneID WHERE T2.Localization = 'plasma membrane'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 genes
【Schema】
# Table: Interactions
[
(GeneID1:TEXT, Primary Key, Examples: [G234064, G234065, G234073]),
(GeneID2:TEXT, Primary Key, Examples: [G234126, G235065, G234371]),
(Type:TEXT, Examples: [Genetic-Physical, Genetic, Physical]),
(Expression_Corr:REAL, Examples: [0.914095071, 0.751584888, 0.823773738])
]
# Table: Classification
[
(GeneID:TEXT, Primary Key, Examples: [G234064, G234065, G234070]),
(Localization:TEXT, Examples: [cytoplasm, cytoskeleton, nucleus])
]
# Table: Genes
[
(GeneID:TEXT, Examples: [G234064, G234065, G234070]),
(Essential:TEXT, Examples: [Essential, Non-Essential, ?]),
(Class:TEXT, Examples: [GTP/GDP-exchange factors (GEFs)]),
(Complex:TEXT, Examples: [Translation complexes]),
(Phenotype:TEXT, Examples: [?]),
(Motif:TEXT, Examples: [PS00824, PS00825, ?]),
(Chromosome:INTEGER, Examples: [1, 2, 3]),
(Function:TEXT),
(Localization:TEXT, Examples: [cytoplasm, cytoskeleton, nucleus])
]
【Foreign keys】
Interactions.GeneID1=Classification.GeneID
Interactions.GeneID2=Classification.GeneID
Genes.GeneID=Classification.GeneID

    【Question】
    How many non-essential genes are located in the nucleus?

    【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.GeneID) FROM Genes AS T1 INNER JOIN Classification AS T2 ON T1.GeneID = T2.GeneID WHERE T2.Localization = 'nucleus' AND T1.Essential = 'Non-Essential'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 genes
【Schema】
# Table: Interactions
[
(GeneID1:TEXT, Primary Key, Examples: [G234064, G234065, G234073]),
(GeneID2:TEXT, Primary Key, Examples: [G234126, G235065, G234371]),
(Type:TEXT, Examples: [Genetic-Physical, Genetic, Physical]),
(Expression_Corr:REAL, Examples: [0.914095071, 0.751584888, 0.823773738])
]
# Table: Classification
[
(GeneID:TEXT, Primary Key, Examples: [G234064, G234065, G234070]),
(Localization:TEXT, Examples: [cytoplasm, cytoskeleton, nucleus])
]
# Table: Genes
[
(GeneID:TEXT, Examples: [G234064, G234065, G234070]),
(Essential:TEXT, Examples: [Essential, Non-Essential, ?]),
(Class:TEXT, Examples: [GTP/GDP-exchange factors (GEFs)]),
(Complex:TEXT, Examples: [Translation complexes]),
(Phenotype:TEXT, Examples: [?]),
(Motif:TEXT, Examples: [PS00824, PS00825, ?]),
(Chromosome:INTEGER, Examples: [1, 2, 3]),
(Function:TEXT),
(Localization:TEXT, Examples: [cytoplasm, cytoskeleton, nucleus])
]
【Foreign keys】
Interactions.GeneID1=Classification.GeneID
Interactions.GeneID2=Classification.GeneID
Genes.GeneID=Classification.GeneID

    【Question】
    Among the genes with nucleic acid metabolism defects, how many of them can be found in the vacuole?

    【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.GeneID) FROM Genes AS T1 INNER JOIN Classification AS T2 ON T1.GeneID = T2.GeneID WHERE T2.Localization = 'vacuole' AND T1.Phenotype = 'Nucleic acid metabolism defects'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 genes
【Schema】
# Table: Interactions
[
(GeneID1:TEXT, Primary Key, Examples: [G234064, G234065, G234073]),
(GeneID2:TEXT, Primary Key, Examples: [G234126, G235065, G234371]),
(Type:TEXT, Examples: [Genetic-Physical, Genetic, Physical]),
(Expression_Corr:REAL, Examples: [0.914095071, 0.751584888, 0.823773738])
]
# Table: Classification
[
(GeneID:TEXT, Primary Key, Examples: [G234064, G234065, G234070]),
(Localization:TEXT, Examples: [cytoplasm, cytoskeleton, nucleus])
]
# Table: Genes
[
(GeneID:TEXT, Examples: [G234064, G234065, G234070]),
(Essential:TEXT, Examples: [Essential, Non-Essential, ?]),
(Class:TEXT, Examples: [GTP/GDP-exchange factors (GEFs)]),
(Complex:TEXT, Examples: [Translation complexes]),
(Phenotype:TEXT, Examples: [?]),
(Motif:TEXT, Examples: [PS00824, PS00825, ?]),
(Chromosome:INTEGER, Examples: [1, 2, 3]),
(Function:TEXT),
(Localization:TEXT, Examples: [cytoplasm, cytoskeleton, nucleus])
]
【Foreign keys】
Interactions.GeneID1=Classification.GeneID
Interactions.GeneID2=Classification.GeneID
Genes.GeneID=Classification.GeneID

    【Question】
    Please list the location of the genes that have the most chromosomes.

    【Evidence】
    

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

SQL: SELECT T2.Localization FROM Genes AS T1 INNER JOIN Classification AS T2 ON T1.GeneID = T2.GeneID ORDER BY T1.Chromosome DESC LIMIT 1
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 genes
【Schema】
# Table: Interactions
[
(GeneID1:TEXT, Primary Key, Examples: [G234064, G234065, G234073]),
(GeneID2:TEXT, Primary Key, Examples: [G234126, G235065, G234371]),
(Type:TEXT, Examples: [Genetic-Physical, Genetic, Physical]),
(Expression_Corr:REAL, Examples: [0.914095071, 0.751584888, 0.823773738])
]
# Table: Classification
[
(GeneID:TEXT, Primary Key, Examples: [G234064, G234065, G234070]),
(Localization:TEXT, Examples: [cytoplasm, cytoskeleton, nucleus])
]
# Table: Genes
[
(GeneID:TEXT, Examples: [G234064, G234065, G234070]),
(Essential:TEXT, Examples: [Essential, Non-Essential, ?]),
(Class:TEXT, Examples: [GTP/GDP-exchange factors (GEFs)]),
(Complex:TEXT, Examples: [Translation complexes]),
(Phenotype:TEXT, Examples: [?]),
(Motif:TEXT, Examples: [PS00824, PS00825, ?]),
(Chromosome:INTEGER, Examples: [1, 2, 3]),
(Function:TEXT),
(Localization:TEXT, Examples: [cytoplasm, cytoskeleton, nucleus])
]
【Foreign keys】
Interactions.GeneID1=Classification.GeneID
Interactions.GeneID2=Classification.GeneID
Genes.GeneID=Classification.GeneID

    【Question】
    Among the pairs of genes that are both located in the nucleus, what is the highest expression correlation score?

    【Evidence】
    

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

SQL: SELECT T2.Expression_Corr FROM Genes AS T1 INNER JOIN Interactions AS T2 ON T1.GeneID = T2.GeneID1 INNER JOIN Genes AS T3 ON T3.GeneID = T2.GeneID2 WHERE T1.Localization = 'nucleus' AND T3.Localization = 'nucleus' ORDER BY T2.Expression_Corr DESC LIMIT 1
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 genes
【Schema】
# Table: Interactions
[
(GeneID1:TEXT, Primary Key, Examples: [G234064, G234065, G234073]),
(GeneID2:TEXT, Primary Key, Examples: [G234126, G235065, G234371]),
(Type:TEXT, Examples: [Genetic-Physical, Genetic, Physical]),
(Expression_Corr:REAL, Examples: [0.914095071, 0.751584888, 0.823773738])
]
# Table: Classification
[
(GeneID:TEXT, Primary Key, Examples: [G234064, G234065, G234070]),
(Localization:TEXT, Examples: [cytoplasm, cytoskeleton, nucleus])
]
# Table: Genes
[
(GeneID:TEXT, Examples: [G234064, G234065, G234070]),
(Essential:TEXT, Examples: [Essential, Non-Essential, ?]),
(Class:TEXT, Examples: [GTP/GDP-exchange factors (GEFs)]),
(Complex:TEXT, Examples: [Translation complexes]),
(Phenotype:TEXT, Examples: [?]),
(Motif:TEXT, Examples: [PS00824, PS00825, ?]),
(Chromosome:INTEGER, Examples: [1, 2, 3]),
(Function:TEXT),
(Localization:TEXT, Examples: [cytoplasm, cytoskeleton, nucleus])
]
【Foreign keys】
Interactions.GeneID1=Classification.GeneID
Interactions.GeneID2=Classification.GeneID
Genes.GeneID=Classification.GeneID

    【Question】
    What are the functions of the pair of genes that have the lowest expression correlation score?a

    【Evidence】
    

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

SQL: SELECT T1.Function FROM Genes AS T1 INNER JOIN Interactions AS T2 ON T1.GeneID = T2.GeneID1 ORDER BY T2.Expression_Corr ASC LIMIT 1
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 genes
【Schema】
# Table: Interactions
[
(GeneID1:TEXT, Primary Key, Examples: [G234064, G234065, G234073]),
(GeneID2:TEXT, Primary Key, Examples: [G234126, G235065, G234371]),
(Type:TEXT, Examples: [Genetic-Physical, Genetic, Physical]),
(Expression_Corr:REAL, Examples: [0.914095071, 0.751584888, 0.823773738])
]
# Table: Classification
[
(GeneID:TEXT, Primary Key, Examples: [G234064, G234065, G234070]),
(Localization:TEXT, Examples: [cytoplasm, cytoskeleton, nucleus])
]
# Table: Genes
[
(GeneID:TEXT, Examples: [G234064, G234065, G234070]),
(Essential:TEXT, Examples: [Essential, Non-Essential, ?]),
(Class:TEXT, Examples: [GTP/GDP-exchange factors (GEFs)]),
(Complex:TEXT, Examples: [Translation complexes]),
(Phenotype:TEXT, Examples: [?]),
(Motif:TEXT, Examples: [PS00824, PS00825, ?]),
(Chromosome:INTEGER, Examples: [1, 2, 3]),
(Function:TEXT),
(Localization:TEXT, Examples: [cytoplasm, cytoskeleton, nucleus])
]
【Foreign keys】
Interactions.GeneID1=Classification.GeneID
Interactions.GeneID2=Classification.GeneID
Genes.GeneID=Classification.GeneID

    【Question】
    Among the pairs of genes that are not from the class of motorproteins, how many of them are negatively correlated? If Expression_Corr < 0, it means the negatively correlated

    【Evidence】
    If Expression_Corr < 0, it means the negatively correlated

    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.GeneID) FROM Genes AS T1 INNER JOIN Interactions AS T2 ON T1.GeneID = T2.GeneID1 WHERE T2.Expression_Corr < 0 AND T1.Class = 'Motorproteins'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 genes
【Schema】
# Table: Interactions
[
(GeneID1:TEXT, Primary Key, Examples: [G234064, G234065, G234073]),
(GeneID2:TEXT, Primary Key, Examples: [G234126, G235065, G234371]),
(Type:TEXT, Examples: [Genetic-Physical, Genetic, Physical]),
(Expression_Corr:REAL, Examples: [0.914095071, 0.751584888, 0.823773738])
]
# Table: Classification
[
(GeneID:TEXT, Primary Key, Examples: [G234064, G234065, G234070]),
(Localization:TEXT, Examples: [cytoplasm, cytoskeleton, nucleus])
]
# Table: Genes
[
(GeneID:TEXT, Examples: [G234064, G234065, G234070]),
(Essential:TEXT, Examples: [Essential, Non-Essential, ?]),
(Class:TEXT, Examples: [GTP/GDP-exchange factors (GEFs)]),
(Complex:TEXT, Examples: [Translation complexes]),
(Phenotype:TEXT, Examples: [?]),
(Motif:TEXT, Examples: [PS00824, PS00825, ?]),
(Chromosome:INTEGER, Examples: [1, 2, 3]),
(Function:TEXT),
(Localization:TEXT, Examples: [cytoplasm, cytoskeleton, nucleus])
]
【Foreign keys】
Interactions.GeneID1=Classification.GeneID
Interactions.GeneID2=Classification.GeneID
Genes.GeneID=Classification.GeneID

    【Question】
    For the pairs of genes with one having 8 chromosomes and the other having 6 chromosomes, what is the highest expression correlation score?

    【Evidence】
    

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

SQL: SELECT T2.Expression_Corr FROM Genes AS T1 INNER JOIN Interactions AS T2 ON T1.GeneID = T2.GeneID1 WHERE T1.Chromosome = 6 OR T1.Chromosome = 8 ORDER BY T2.Expression_Corr DESC LIMIT 1
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 genes
【Schema】
# Table: Interactions
[
(GeneID1:TEXT, Primary Key, Examples: [G234064, G234065, G234073]),
(GeneID2:TEXT, Primary Key, Examples: [G234126, G235065, G234371]),
(Type:TEXT, Examples: [Genetic-Physical, Genetic, Physical]),
(Expression_Corr:REAL, Examples: [0.914095071, 0.751584888, 0.823773738])
]
# Table: Classification
[
(GeneID:TEXT, Primary Key, Examples: [G234064, G234065, G234070]),
(Localization:TEXT, Examples: [cytoplasm, cytoskeleton, nucleus])
]
# Table: Genes
[
(GeneID:TEXT, Examples: [G234064, G234065, G234070]),
(Essential:TEXT, Examples: [Essential, Non-Essential, ?]),
(Class:TEXT, Examples: [GTP/GDP-exchange factors (GEFs)]),
(Complex:TEXT, Examples: [Translation complexes]),
(Phenotype:TEXT, Examples: [?]),
(Motif:TEXT, Examples: [PS00824, PS00825, ?]),
(Chromosome:INTEGER, Examples: [1, 2, 3]),
(Function:TEXT),
(Localization:TEXT, Examples: [cytoplasm, cytoskeleton, nucleus])
]
【Foreign keys】
Interactions.GeneID1=Classification.GeneID
Interactions.GeneID2=Classification.GeneID
Genes.GeneID=Classification.GeneID

    【Question】
    Please list the motif of the genes that are located in the cytoplasm and have 7 chromosomes.

    【Evidence】
    

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

SQL: SELECT T2.GeneID1, T2.GeneID2 FROM Genes AS T1 INNER JOIN Interactions AS T2 ON T1.GeneID = T2.GeneID1 WHERE T1.Localization = 'cytoplasm' AND T1.Chromosome = 7
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 genes
【Schema】
# Table: Interactions
[
(GeneID1:TEXT, Primary Key, Examples: [G234064, G234065, G234073]),
(GeneID2:TEXT, Primary Key, Examples: [G234126, G235065, G234371]),
(Type:TEXT, Examples: [Genetic-Physical, Genetic, Physical]),
(Expression_Corr:REAL, Examples: [0.914095071, 0.751584888, 0.823773738])
]
# Table: Classification
[
(GeneID:TEXT, Primary Key, Examples: [G234064, G234065, G234070]),
(Localization:TEXT, Examples: [cytoplasm, cytoskeleton, nucleus])
]
# Table: Genes
[
(GeneID:TEXT, Examples: [G234064, G234065, G234070]),
(Essential:TEXT, Examples: [Essential, Non-Essential, ?]),
(Class:TEXT, Examples: [GTP/GDP-exchange factors (GEFs)]),
(Complex:TEXT, Examples: [Translation complexes]),
(Phenotype:TEXT, Examples: [?]),
(Motif:TEXT, Examples: [PS00824, PS00825, ?]),
(Chromosome:INTEGER, Examples: [1, 2, 3]),
(Function:TEXT),
(Localization:TEXT, Examples: [cytoplasm, cytoskeleton, nucleus])
]
【Foreign keys】
Interactions.GeneID1=Classification.GeneID
Interactions.GeneID2=Classification.GeneID
Genes.GeneID=Classification.GeneID

    【Question】
    For the non-essential genes whose functions are transcription, how many of them are not located in the cytoplasm?

    【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.GeneID) FROM Genes AS T1 INNER JOIN Interactions AS T2 ON T1.GeneID = T2.GeneID1 WHERE T1.Localization != 'cytoplasm' AND T1.Function = 'TRANSCRIPTION' AND T1.Essential = 'NON-Essential'