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】 ice_hockey_draft
【Schema】
# Table: SeasonStatus
[
(ELITEID:INTEGER, Examples: [3667, 3668, 3669]),
(SEASON:TEXT, Examples: [1997-1998, 1999-2000, 1998-1999]),
(TEAM:TEXT, Examples: [Rimouski Oceanic, Canada U20, Plymouth Whalers]),
(LEAGUE:TEXT, Examples: [QMJHL, WJC-20, OHL]),
(GAMETYPE:TEXT, Examples: [Regular Season, Playoffs]),
(GP:INTEGER, Examples: [58, 18, 7]),
(G:INTEGER, Examples: [44, 15, 1]),
(A:INTEGER, Examples: [71, 26, 1]),
(P:INTEGER, Examples: [115, 41, 2]),
(PIM:INTEGER, Examples: [117, 46, 4]),
(PLUSMINUS:INTEGER, Examples: [27, 4, 0])
]
# Table: PlayerInfo
[
(ELITEID:INTEGER, Primary Key, Examples: [9, 18, 27]),
(PlayerName:TEXT, Examples: [David Bornhammar, David Printz, Yared Hagos]),
(birthdate:TEXT, Examples: [1981-06-15, 1980-07-24, 1983-03-27]),
(birthyear:DATE),
(birthmonth:INTEGER, Examples: [6, 7, 3]),
(birthday:INTEGER, Examples: [15, 24, 27]),
(birthplace:TEXT, Examples: [Lidingo, SWE, Stockholm, SWE, Ostersund, SWE]),
(nation:TEXT, Examples: [Sweden, Austria, Slovakia]),
(height:INTEGER, Examples: [73, 76, 72]),
(weight:INTEGER, Examples: [198, 220, 218]),
(position_info:TEXT, Examples: [D, C, LW/C]),
(shoots:TEXT, Examples: [L, R, -]),
(draftyear:INTEGER, Examples: [1999, 2001, 2002]),
(draftround:INTEGER, Examples: [7, 3, 5]),
(overall:INTEGER, Examples: [192, 225, 70]),
(overallby:TEXT, Examples: [Washington Capitals, Philadelphia Flyers, Dallas Stars]),
(CSS_rank:INTEGER, Examples: [192, 176, 24]),
(sum_7yr_GP:INTEGER, Examples: [0, 13, 6]),
(sum_7yr_TOI:INTEGER, Examples: [0, 84, 42]),
(GP_greater_than_0:TEXT, Examples: [no, yes])
]
# Table: weight_info
[
(weight_id:INTEGER, Primary Key, Examples: [154, 159, 161]),
(weight_in_kg:INTEGER, Examples: [70, 72, 73]),
(weight_in_lbs:INTEGER, Examples: [154, 159, 161])
]
# Table: height_info
[
(height_id:INTEGER, Primary Key, Examples: [65, 67, 68]),
(height_in_cm:INTEGER, Examples: [165, 170, 172]),
(height_in_inch:TEXT, Examples: [5'5", 5'7", 5'8"])
]
【Foreign keys】
SeasonStatus.ELITEID=PlayerInfo.ELITEID
PlayerInfo.height=height_info.height_id
PlayerInfo.weight=weight_info.weight_id

    【Question】
    Which country do most players of team Plymouth Whalers come from? country and nation are synonyms; country where most players come from refers to MAX(COUNT(nation WHERE TEAM = 'Plymouth Whalers')); players refers to PlayerName; team Plymouth Whalers refers to TEAM = 'Plymouth Whalers';

    【Evidence】
    country and nation are synonyms; country where most players come from refers to MAX(COUNT(nation WHERE TEAM = 'Plymouth Whalers')); players refers to PlayerName; team Plymouth Whalers refers to TEAM = 'Plymouth Whalers';

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

SQL: SELECT T.nation FROM ( SELECT T1.nation, COUNT(T1.ELITEID) FROM PlayerInfo AS T1 INNER JOIN SeasonStatus AS T2 ON T1.ELITEID = T2.ELITEID WHERE T2.TEAM = 'Plymouth Whalers' GROUP BY T1.nation ORDER BY COUNT(T1.ELITEID) DESC LIMIT 1 ) AS T
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 ice_hockey_draft
【Schema】
# Table: SeasonStatus
[
(ELITEID:INTEGER, Examples: [3667, 3668, 3669]),
(SEASON:TEXT, Examples: [1997-1998, 1999-2000, 1998-1999]),
(TEAM:TEXT, Examples: [Rimouski Oceanic, Canada U20, Plymouth Whalers]),
(LEAGUE:TEXT, Examples: [QMJHL, WJC-20, OHL]),
(GAMETYPE:TEXT, Examples: [Regular Season, Playoffs]),
(GP:INTEGER, Examples: [58, 18, 7]),
(G:INTEGER, Examples: [44, 15, 1]),
(A:INTEGER, Examples: [71, 26, 1]),
(P:INTEGER, Examples: [115, 41, 2]),
(PIM:INTEGER, Examples: [117, 46, 4]),
(PLUSMINUS:INTEGER, Examples: [27, 4, 0])
]
# Table: PlayerInfo
[
(ELITEID:INTEGER, Primary Key, Examples: [9, 18, 27]),
(PlayerName:TEXT, Examples: [David Bornhammar, David Printz, Yared Hagos]),
(birthdate:TEXT, Examples: [1981-06-15, 1980-07-24, 1983-03-27]),
(birthyear:DATE),
(birthmonth:INTEGER, Examples: [6, 7, 3]),
(birthday:INTEGER, Examples: [15, 24, 27]),
(birthplace:TEXT, Examples: [Lidingo, SWE, Stockholm, SWE, Ostersund, SWE]),
(nation:TEXT, Examples: [Sweden, Austria, Slovakia]),
(height:INTEGER, Examples: [73, 76, 72]),
(weight:INTEGER, Examples: [198, 220, 218]),
(position_info:TEXT, Examples: [D, C, LW/C]),
(shoots:TEXT, Examples: [L, R, -]),
(draftyear:INTEGER, Examples: [1999, 2001, 2002]),
(draftround:INTEGER, Examples: [7, 3, 5]),
(overall:INTEGER, Examples: [192, 225, 70]),
(overallby:TEXT, Examples: [Washington Capitals, Philadelphia Flyers, Dallas Stars]),
(CSS_rank:INTEGER, Examples: [192, 176, 24]),
(sum_7yr_GP:INTEGER, Examples: [0, 13, 6]),
(sum_7yr_TOI:INTEGER, Examples: [0, 84, 42]),
(GP_greater_than_0:TEXT, Examples: [no, yes])
]
# Table: weight_info
[
(weight_id:INTEGER, Primary Key, Examples: [154, 159, 161]),
(weight_in_kg:INTEGER, Examples: [70, 72, 73]),
(weight_in_lbs:INTEGER, Examples: [154, 159, 161])
]
# Table: height_info
[
(height_id:INTEGER, Primary Key, Examples: [65, 67, 68]),
(height_in_cm:INTEGER, Examples: [165, 170, 172]),
(height_in_inch:TEXT, Examples: [5'5", 5'7", 5'8"])
]
【Foreign keys】
SeasonStatus.ELITEID=PlayerInfo.ELITEID
PlayerInfo.height=height_info.height_id
PlayerInfo.weight=weight_info.weight_id

    【Question】
    Who had the most assists of team Plymouth Whalers in the 1999-2000 season? who refers to PlayerName; most assists refers to MAX(A); team Plymouth Whalers refers to TEAM = 'Plymouth Whalers'; 1999-2000 season refers to SEASON = '1999-2000';

    【Evidence】
    who refers to PlayerName; most assists refers to MAX(A); team Plymouth Whalers refers to TEAM = 'Plymouth Whalers'; 1999-2000 season refers to SEASON = '1999-2000';

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

SQL: SELECT T1.PlayerName FROM PlayerInfo AS T1 INNER JOIN SeasonStatus AS T2 ON T1.ELITEID = T2.ELITEID WHERE T2.TEAM = 'Plymouth Whalers' AND T2.SEASON = '1999-2000' ORDER BY T2.A DESC LIMIT 1
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 ice_hockey_draft
【Schema】
# Table: SeasonStatus
[
(ELITEID:INTEGER, Examples: [3667, 3668, 3669]),
(SEASON:TEXT, Examples: [1997-1998, 1999-2000, 1998-1999]),
(TEAM:TEXT, Examples: [Rimouski Oceanic, Canada U20, Plymouth Whalers]),
(LEAGUE:TEXT, Examples: [QMJHL, WJC-20, OHL]),
(GAMETYPE:TEXT, Examples: [Regular Season, Playoffs]),
(GP:INTEGER, Examples: [58, 18, 7]),
(G:INTEGER, Examples: [44, 15, 1]),
(A:INTEGER, Examples: [71, 26, 1]),
(P:INTEGER, Examples: [115, 41, 2]),
(PIM:INTEGER, Examples: [117, 46, 4]),
(PLUSMINUS:INTEGER, Examples: [27, 4, 0])
]
# Table: PlayerInfo
[
(ELITEID:INTEGER, Primary Key, Examples: [9, 18, 27]),
(PlayerName:TEXT, Examples: [David Bornhammar, David Printz, Yared Hagos]),
(birthdate:TEXT, Examples: [1981-06-15, 1980-07-24, 1983-03-27]),
(birthyear:DATE),
(birthmonth:INTEGER, Examples: [6, 7, 3]),
(birthday:INTEGER, Examples: [15, 24, 27]),
(birthplace:TEXT, Examples: [Lidingo, SWE, Stockholm, SWE, Ostersund, SWE]),
(nation:TEXT, Examples: [Sweden, Austria, Slovakia]),
(height:INTEGER, Examples: [73, 76, 72]),
(weight:INTEGER, Examples: [198, 220, 218]),
(position_info:TEXT, Examples: [D, C, LW/C]),
(shoots:TEXT, Examples: [L, R, -]),
(draftyear:INTEGER, Examples: [1999, 2001, 2002]),
(draftround:INTEGER, Examples: [7, 3, 5]),
(overall:INTEGER, Examples: [192, 225, 70]),
(overallby:TEXT, Examples: [Washington Capitals, Philadelphia Flyers, Dallas Stars]),
(CSS_rank:INTEGER, Examples: [192, 176, 24]),
(sum_7yr_GP:INTEGER, Examples: [0, 13, 6]),
(sum_7yr_TOI:INTEGER, Examples: [0, 84, 42]),
(GP_greater_than_0:TEXT, Examples: [no, yes])
]
# Table: weight_info
[
(weight_id:INTEGER, Primary Key, Examples: [154, 159, 161]),
(weight_in_kg:INTEGER, Examples: [70, 72, 73]),
(weight_in_lbs:INTEGER, Examples: [154, 159, 161])
]
# Table: height_info
[
(height_id:INTEGER, Primary Key, Examples: [65, 67, 68]),
(height_in_cm:INTEGER, Examples: [165, 170, 172]),
(height_in_inch:TEXT, Examples: [5'5", 5'7", 5'8"])
]
【Foreign keys】
SeasonStatus.ELITEID=PlayerInfo.ELITEID
PlayerInfo.height=height_info.height_id
PlayerInfo.weight=weight_info.weight_id

    【Question】
    Indicate the height of all players from team Oshawa Generals in inches. height in inches refers to height_in_inch; players refers to PlayerName; team Oshawa Generals refers to TEAM = 'Oshawa Generals';

    【Evidence】
    height in inches refers to height_in_inch; players refers to PlayerName; team Oshawa Generals refers to TEAM = 'Oshawa Generals';

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

SQL: SELECT T3.height_in_inch FROM PlayerInfo AS T1 INNER JOIN SeasonStatus AS T2 ON T1.ELITEID = T2.ELITEID INNER JOIN height_info AS T3 ON T1.height = T3.height_id WHERE T2.TEAM = 'Oshawa Generals'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 ice_hockey_draft
【Schema】
# Table: SeasonStatus
[
(ELITEID:INTEGER, Examples: [3667, 3668, 3669]),
(SEASON:TEXT, Examples: [1997-1998, 1999-2000, 1998-1999]),
(TEAM:TEXT, Examples: [Rimouski Oceanic, Canada U20, Plymouth Whalers]),
(LEAGUE:TEXT, Examples: [QMJHL, WJC-20, OHL]),
(GAMETYPE:TEXT, Examples: [Regular Season, Playoffs]),
(GP:INTEGER, Examples: [58, 18, 7]),
(G:INTEGER, Examples: [44, 15, 1]),
(A:INTEGER, Examples: [71, 26, 1]),
(P:INTEGER, Examples: [115, 41, 2]),
(PIM:INTEGER, Examples: [117, 46, 4]),
(PLUSMINUS:INTEGER, Examples: [27, 4, 0])
]
# Table: PlayerInfo
[
(ELITEID:INTEGER, Primary Key, Examples: [9, 18, 27]),
(PlayerName:TEXT, Examples: [David Bornhammar, David Printz, Yared Hagos]),
(birthdate:TEXT, Examples: [1981-06-15, 1980-07-24, 1983-03-27]),
(birthyear:DATE),
(birthmonth:INTEGER, Examples: [6, 7, 3]),
(birthday:INTEGER, Examples: [15, 24, 27]),
(birthplace:TEXT, Examples: [Lidingo, SWE, Stockholm, SWE, Ostersund, SWE]),
(nation:TEXT, Examples: [Sweden, Austria, Slovakia]),
(height:INTEGER, Examples: [73, 76, 72]),
(weight:INTEGER, Examples: [198, 220, 218]),
(position_info:TEXT, Examples: [D, C, LW/C]),
(shoots:TEXT, Examples: [L, R, -]),
(draftyear:INTEGER, Examples: [1999, 2001, 2002]),
(draftround:INTEGER, Examples: [7, 3, 5]),
(overall:INTEGER, Examples: [192, 225, 70]),
(overallby:TEXT, Examples: [Washington Capitals, Philadelphia Flyers, Dallas Stars]),
(CSS_rank:INTEGER, Examples: [192, 176, 24]),
(sum_7yr_GP:INTEGER, Examples: [0, 13, 6]),
(sum_7yr_TOI:INTEGER, Examples: [0, 84, 42]),
(GP_greater_than_0:TEXT, Examples: [no, yes])
]
# Table: weight_info
[
(weight_id:INTEGER, Primary Key, Examples: [154, 159, 161]),
(weight_in_kg:INTEGER, Examples: [70, 72, 73]),
(weight_in_lbs:INTEGER, Examples: [154, 159, 161])
]
# Table: height_info
[
(height_id:INTEGER, Primary Key, Examples: [65, 67, 68]),
(height_in_cm:INTEGER, Examples: [165, 170, 172]),
(height_in_inch:TEXT, Examples: [5'5", 5'7", 5'8"])
]
【Foreign keys】
SeasonStatus.ELITEID=PlayerInfo.ELITEID
PlayerInfo.height=height_info.height_id
PlayerInfo.weight=weight_info.weight_id

    【Question】
    Who is the oldest player that participated in OHL league in the 1997 - 2000 season? oldest player refers to MIN(birthdate); OHL league refers to LEAGUE = 'OHL'; 1997-2000 season refers to SEASON = '1997-2000';

    【Evidence】
    oldest player refers to MIN(birthdate); OHL league refers to LEAGUE = 'OHL'; 1997-2000 season refers to SEASON = '1997-2000';

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

SQL: SELECT T1.PlayerName FROM PlayerInfo AS T1 INNER JOIN SeasonStatus AS T2 ON T1.ELITEID = T2.ELITEID WHERE T2.LEAGUE = 'OHL' AND T2.SEASON = '1999-2000' ORDER BY T1.birthdate LIMIT 1
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 ice_hockey_draft
【Schema】
# Table: SeasonStatus
[
(ELITEID:INTEGER, Examples: [3667, 3668, 3669]),
(SEASON:TEXT, Examples: [1997-1998, 1999-2000, 1998-1999]),
(TEAM:TEXT, Examples: [Rimouski Oceanic, Canada U20, Plymouth Whalers]),
(LEAGUE:TEXT, Examples: [QMJHL, WJC-20, OHL]),
(GAMETYPE:TEXT, Examples: [Regular Season, Playoffs]),
(GP:INTEGER, Examples: [58, 18, 7]),
(G:INTEGER, Examples: [44, 15, 1]),
(A:INTEGER, Examples: [71, 26, 1]),
(P:INTEGER, Examples: [115, 41, 2]),
(PIM:INTEGER, Examples: [117, 46, 4]),
(PLUSMINUS:INTEGER, Examples: [27, 4, 0])
]
# Table: PlayerInfo
[
(ELITEID:INTEGER, Primary Key, Examples: [9, 18, 27]),
(PlayerName:TEXT, Examples: [David Bornhammar, David Printz, Yared Hagos]),
(birthdate:TEXT, Examples: [1981-06-15, 1980-07-24, 1983-03-27]),
(birthyear:DATE),
(birthmonth:INTEGER, Examples: [6, 7, 3]),
(birthday:INTEGER, Examples: [15, 24, 27]),
(birthplace:TEXT, Examples: [Lidingo, SWE, Stockholm, SWE, Ostersund, SWE]),
(nation:TEXT, Examples: [Sweden, Austria, Slovakia]),
(height:INTEGER, Examples: [73, 76, 72]),
(weight:INTEGER, Examples: [198, 220, 218]),
(position_info:TEXT, Examples: [D, C, LW/C]),
(shoots:TEXT, Examples: [L, R, -]),
(draftyear:INTEGER, Examples: [1999, 2001, 2002]),
(draftround:INTEGER, Examples: [7, 3, 5]),
(overall:INTEGER, Examples: [192, 225, 70]),
(overallby:TEXT, Examples: [Washington Capitals, Philadelphia Flyers, Dallas Stars]),
(CSS_rank:INTEGER, Examples: [192, 176, 24]),
(sum_7yr_GP:INTEGER, Examples: [0, 13, 6]),
(sum_7yr_TOI:INTEGER, Examples: [0, 84, 42]),
(GP_greater_than_0:TEXT, Examples: [no, yes])
]
# Table: weight_info
[
(weight_id:INTEGER, Primary Key, Examples: [154, 159, 161]),
(weight_in_kg:INTEGER, Examples: [70, 72, 73]),
(weight_in_lbs:INTEGER, Examples: [154, 159, 161])
]
# Table: height_info
[
(height_id:INTEGER, Primary Key, Examples: [65, 67, 68]),
(height_in_cm:INTEGER, Examples: [165, 170, 172]),
(height_in_inch:TEXT, Examples: [5'5", 5'7", 5'8"])
]
【Foreign keys】
SeasonStatus.ELITEID=PlayerInfo.ELITEID
PlayerInfo.height=height_info.height_id
PlayerInfo.weight=weight_info.weight_id

    【Question】
    Who is the tallest player in team USA U20? tallest refers to MAX(height_in_cm); 
player refers to PlayerName; team USA U20 refers to TEAM = 'USA U20';

    【Evidence】
    tallest refers to MAX(height_in_cm); 
player refers to PlayerName; team USA U20 refers to TEAM = 'USA U20';

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

SQL: SELECT T.PlayerName FROM ( SELECT T1.PlayerName, T3.height_in_cm FROM PlayerInfo AS T1 INNER JOIN SeasonStatus AS T2 ON T1.ELITEID = T2.ELITEID INNER JOIN height_info AS T3 ON T1.height = T3.height_id WHERE T2.TEAM = 'USA U20' ORDER BY T3.height_in_cm DESC ) AS T WHERE T.height_in_cm = ( SELECT MAX(T3.height_in_cm) FROM PlayerInfo AS T1 INNER JOIN SeasonStatus AS T2 ON T1.ELITEID = T2.ELITEID INNER JOIN height_info AS T3 ON T1.height = T3.height_id WHERE T2.TEAM = 'USA U20' )
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 ice_hockey_draft
【Schema】
# Table: SeasonStatus
[
(ELITEID:INTEGER, Examples: [3667, 3668, 3669]),
(SEASON:TEXT, Examples: [1997-1998, 1999-2000, 1998-1999]),
(TEAM:TEXT, Examples: [Rimouski Oceanic, Canada U20, Plymouth Whalers]),
(LEAGUE:TEXT, Examples: [QMJHL, WJC-20, OHL]),
(GAMETYPE:TEXT, Examples: [Regular Season, Playoffs]),
(GP:INTEGER, Examples: [58, 18, 7]),
(G:INTEGER, Examples: [44, 15, 1]),
(A:INTEGER, Examples: [71, 26, 1]),
(P:INTEGER, Examples: [115, 41, 2]),
(PIM:INTEGER, Examples: [117, 46, 4]),
(PLUSMINUS:INTEGER, Examples: [27, 4, 0])
]
# Table: PlayerInfo
[
(ELITEID:INTEGER, Primary Key, Examples: [9, 18, 27]),
(PlayerName:TEXT, Examples: [David Bornhammar, David Printz, Yared Hagos]),
(birthdate:TEXT, Examples: [1981-06-15, 1980-07-24, 1983-03-27]),
(birthyear:DATE),
(birthmonth:INTEGER, Examples: [6, 7, 3]),
(birthday:INTEGER, Examples: [15, 24, 27]),
(birthplace:TEXT, Examples: [Lidingo, SWE, Stockholm, SWE, Ostersund, SWE]),
(nation:TEXT, Examples: [Sweden, Austria, Slovakia]),
(height:INTEGER, Examples: [73, 76, 72]),
(weight:INTEGER, Examples: [198, 220, 218]),
(position_info:TEXT, Examples: [D, C, LW/C]),
(shoots:TEXT, Examples: [L, R, -]),
(draftyear:INTEGER, Examples: [1999, 2001, 2002]),
(draftround:INTEGER, Examples: [7, 3, 5]),
(overall:INTEGER, Examples: [192, 225, 70]),
(overallby:TEXT, Examples: [Washington Capitals, Philadelphia Flyers, Dallas Stars]),
(CSS_rank:INTEGER, Examples: [192, 176, 24]),
(sum_7yr_GP:INTEGER, Examples: [0, 13, 6]),
(sum_7yr_TOI:INTEGER, Examples: [0, 84, 42]),
(GP_greater_than_0:TEXT, Examples: [no, yes])
]
# Table: weight_info
[
(weight_id:INTEGER, Primary Key, Examples: [154, 159, 161]),
(weight_in_kg:INTEGER, Examples: [70, 72, 73]),
(weight_in_lbs:INTEGER, Examples: [154, 159, 161])
]
# Table: height_info
[
(height_id:INTEGER, Primary Key, Examples: [65, 67, 68]),
(height_in_cm:INTEGER, Examples: [165, 170, 172]),
(height_in_inch:TEXT, Examples: [5'5", 5'7", 5'8"])
]
【Foreign keys】
SeasonStatus.ELITEID=PlayerInfo.ELITEID
PlayerInfo.height=height_info.height_id
PlayerInfo.weight=weight_info.weight_id

    【Question】
    Calculate the percentage of penalty minutes of Swedish players in OHL league among all players. percentage = MULTIPLY(DIVIDE(SUM(PIM WHERE nation = 'Sweden'), COUNT(ELITEID) WHERE LEAGUE = 'OHL'), 100); Swedish refers to nation = 'Sweden'; players refers to PlayerName; OHL league refers to LEAGUE = 'OHL';

    【Evidence】
    percentage = MULTIPLY(DIVIDE(SUM(PIM WHERE nation = 'Sweden'), COUNT(ELITEID) WHERE LEAGUE = 'OHL'), 100); Swedish refers to nation = 'Sweden'; players refers to PlayerName; OHL league refers to LEAGUE = 'OHL';

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

SQL: SELECT CAST(COUNT(CASE WHEN T1.nation = 'Sweden' THEN T2.PIM ELSE NULL END) AS REAL) * 100 / COUNT(*) FROM PlayerInfo AS T1 INNER JOIN SeasonStatus AS T2 ON T1.ELITEID = T2.ELITEID WHERE T2.LEAGUE = 'OHL'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 image_and_language
【Schema】
# Table: ATT_CLASSES
[
(ATT_CLASS_ID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(ATT_CLASS:TEXT, Examples: [building s, indoors, cluttered])
]
# Table: IMG_OBJ_ATT
[
(IMG_ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(ATT_CLASS_ID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(OBJ_SAMPLE_ID:INTEGER, Primary Key, Examples: [21, 22, 23])
]
# Table: IMG_OBJ
[
(IMG_ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(OBJ_SAMPLE_ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(OBJ_CLASS_ID:INTEGER, Examples: [298, 246, 293]),
(X:INTEGER, Examples: [0, 78, 1]),
(Y:INTEGER, Examples: [0, 308, 283]),
(W:INTEGER, Examples: [799, 722, 222]),
(H:INTEGER, Examples: [557, 290, 538])
]
# Table: OBJ_CLASSES
[
(OBJ_CLASS_ID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(OBJ_CLASS:TEXT, Examples: [awning, goggles, dot])
]
# Table: IMG_REL
[
(IMG_ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(PRED_CLASS_ID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(OBJ1_SAMPLE_ID:INTEGER, Primary Key, Examples: [13, 12, 4]),
(OBJ2_SAMPLE_ID:INTEGER, Primary Key, Examples: [1, 34, 5])
]
# Table: PRED_CLASSES
[
(PRED_CLASS_ID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(PRED_CLASS:TEXT, Examples: [playing on, looking a, to left of])
]
【Foreign keys】
IMG_OBJ_ATT.ATT_CLASS_ID=ATT_CLASSES.ATT_CLASS_ID
IMG_OBJ_ATT.IMG_ID=IMG_OBJ.IMG_ID
IMG_OBJ_ATT.OBJ_SAMPLE_ID=IMG_OBJ.OBJ_SAMPLE_ID
IMG_OBJ.OBJ_CLASS_ID=OBJ_CLASSES.OBJ_CLASS_ID
IMG_REL.PRED_CLASS_ID=PRED_CLASSES.PRED_CLASS_ID
IMG_REL.IMG_ID=IMG_OBJ.IMG_ID
IMG_REL.OBJ1_SAMPLE_ID=IMG_OBJ.OBJ_SAMPLE_ID
IMG_REL.IMG_ID=IMG_OBJ.IMG_ID
IMG_REL.OBJ2_SAMPLE_ID=IMG_OBJ.OBJ_SAMPLE_ID

    【Question】
    How many object samples are there in image no.1? object samples refers to OBJ_SAMPLE_ID; image no.1 refers to IMG_ID = 1

    【Evidence】
    object samples refers to OBJ_SAMPLE_ID; image no.1 refers to IMG_ID = 1

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

SQL: SELECT COUNT(OBJ_SAMPLE_ID) FROM IMG_OBJ WHERE IMG_ID = 1
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 image_and_language
【Schema】
# Table: ATT_CLASSES
[
(ATT_CLASS_ID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(ATT_CLASS:TEXT, Examples: [building s, indoors, cluttered])
]
# Table: IMG_OBJ_ATT
[
(IMG_ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(ATT_CLASS_ID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(OBJ_SAMPLE_ID:INTEGER, Primary Key, Examples: [21, 22, 23])
]
# Table: IMG_OBJ
[
(IMG_ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(OBJ_SAMPLE_ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(OBJ_CLASS_ID:INTEGER, Examples: [298, 246, 293]),
(X:INTEGER, Examples: [0, 78, 1]),
(Y:INTEGER, Examples: [0, 308, 283]),
(W:INTEGER, Examples: [799, 722, 222]),
(H:INTEGER, Examples: [557, 290, 538])
]
# Table: OBJ_CLASSES
[
(OBJ_CLASS_ID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(OBJ_CLASS:TEXT, Examples: [awning, goggles, dot])
]
# Table: IMG_REL
[
(IMG_ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(PRED_CLASS_ID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(OBJ1_SAMPLE_ID:INTEGER, Primary Key, Examples: [13, 12, 4]),
(OBJ2_SAMPLE_ID:INTEGER, Primary Key, Examples: [1, 34, 5])
]
# Table: PRED_CLASSES
[
(PRED_CLASS_ID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(PRED_CLASS:TEXT, Examples: [playing on, looking a, to left of])
]
【Foreign keys】
IMG_OBJ_ATT.ATT_CLASS_ID=ATT_CLASSES.ATT_CLASS_ID
IMG_OBJ_ATT.IMG_ID=IMG_OBJ.IMG_ID
IMG_OBJ_ATT.OBJ_SAMPLE_ID=IMG_OBJ.OBJ_SAMPLE_ID
IMG_OBJ.OBJ_CLASS_ID=OBJ_CLASSES.OBJ_CLASS_ID
IMG_REL.PRED_CLASS_ID=PRED_CLASSES.PRED_CLASS_ID
IMG_REL.IMG_ID=IMG_OBJ.IMG_ID
IMG_REL.OBJ1_SAMPLE_ID=IMG_OBJ.OBJ_SAMPLE_ID
IMG_REL.IMG_ID=IMG_OBJ.IMG_ID
IMG_REL.OBJ2_SAMPLE_ID=IMG_OBJ.OBJ_SAMPLE_ID

    【Question】
    How many images have over 20 object samples? over 20 object samples refers to COUNT(OBJ_SAMPLE_ID) > 20

    【Evidence】
    over 20 object samples refers to COUNT(OBJ_SAMPLE_ID) > 20

    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.IMG_ID) FROM ( SELECT IMG_ID FROM IMG_OBJ GROUP BY IMG_ID HAVING COUNT(OBJ_SAMPLE_ID) > 20 ) T1