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】 coinmarketcap
【Schema】
# Table: coins
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(name:TEXT, Examples: [Bitcoin, Litecoin, Namecoin]),
(slug:TEXT, Examples: [bitcoin, litecoin, namecoin]),
(symbol:TEXT, Examples: [BTC, LTC, NMC]),
(status:TEXT, Examples: [active, untracked, inactive]),
(category:TEXT, Examples: [coin, token]),
(description:TEXT),
(subreddit:TEXT, Examples: [bitcoin, litecoin, namecoin]),
(notice:TEXT),
(tags:TEXT),
(tag_names:TEXT),
(website:TEXT),
(platform_id:INTEGER, Examples: [1027, 1765, 1376]),
(date_added:TEXT, Examples: [2013-04-28T00:00:00.000Z]),
(date_launched:TEXT, Examples: [2018-01-16T00:00:00.000Z])
]
# Table: historical
[
(date:DATE, Examples: [2013-04-28]),
(coin_id:INTEGER, Examples: [1, 2, 5]),
(cmc_rank:INTEGER, Examples: [1, 2, 3]),
(market_cap:REAL, Examples: [1488566971.9558687, 74637021.56790735, 7250186.647688276]),
(price:REAL, Examples: [134.210021972656, 4.34840488433838, 0.386524856090546]),
(open:REAL, Examples: [134.44400024414062, 4.366759777069092, 0.3871999979019165]),
(high:REAL, Examples: [147.48800659179688, 4.573599815368652, 0.4247649908065796]),
(low:REAL, Examples: [134.0, 4.225639820098877, 0.37790799140930176]),
(close:REAL, Examples: [144.5399932861328, 4.383900165557861, 0.4088610112667084]),
(time_high:TEXT, Examples: [13:15:01, 13:15:03, 12:45:02]),
(time_low:TEXT, Examples: [05:20:01, 19:25:02, 04:05:04]),
(volume_24h:REAL, Examples: [0.0, 46862728.0, 31112234.0]),
(percent_change_1h:REAL, Examples: [0.639231, 0.799273, -0.934763]),
(percent_change_24h:REAL, Examples: [7.63553, 0.920718, 18.558]),
(percent_change_7d:REAL, Examples: [-13.809, -16.7201, 1.64395]),
(circulating_supply:REAL, Examples: [11091325.0, 17164230.0, 18757362.0]),
(total_supply:REAL, Examples: [11091325.0, 17164230.0, 18757362.0]),
(max_supply:REAL, Examples: [21000000.0, 84000000.0, 42000000.0]),
(num_market_pairs:INTEGER, Examples: [7050, 5146, 382])
]

    【Question】
    When was Lebowskis not opened? when refers to date; not opened refers to open IS NULL

    【Evidence】
    when refers to date; not opened refers to open IS NULL

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

SQL: SELECT DISTINCT T2.date FROM coins AS T1 INNER JOIN historical AS T2 ON T1.id = T2.coin_id WHERE T1.name = 'Lebowskis' AND (T2.open IS NULL OR T2.open = 0)
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 coinmarketcap
【Schema】
# Table: coins
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(name:TEXT, Examples: [Bitcoin, Litecoin, Namecoin]),
(slug:TEXT, Examples: [bitcoin, litecoin, namecoin]),
(symbol:TEXT, Examples: [BTC, LTC, NMC]),
(status:TEXT, Examples: [active, untracked, inactive]),
(category:TEXT, Examples: [coin, token]),
(description:TEXT),
(subreddit:TEXT, Examples: [bitcoin, litecoin, namecoin]),
(notice:TEXT),
(tags:TEXT),
(tag_names:TEXT),
(website:TEXT),
(platform_id:INTEGER, Examples: [1027, 1765, 1376]),
(date_added:TEXT, Examples: [2013-04-28T00:00:00.000Z]),
(date_launched:TEXT, Examples: [2018-01-16T00:00:00.000Z])
]
# Table: historical
[
(date:DATE, Examples: [2013-04-28]),
(coin_id:INTEGER, Examples: [1, 2, 5]),
(cmc_rank:INTEGER, Examples: [1, 2, 3]),
(market_cap:REAL, Examples: [1488566971.9558687, 74637021.56790735, 7250186.647688276]),
(price:REAL, Examples: [134.210021972656, 4.34840488433838, 0.386524856090546]),
(open:REAL, Examples: [134.44400024414062, 4.366759777069092, 0.3871999979019165]),
(high:REAL, Examples: [147.48800659179688, 4.573599815368652, 0.4247649908065796]),
(low:REAL, Examples: [134.0, 4.225639820098877, 0.37790799140930176]),
(close:REAL, Examples: [144.5399932861328, 4.383900165557861, 0.4088610112667084]),
(time_high:TEXT, Examples: [13:15:01, 13:15:03, 12:45:02]),
(time_low:TEXT, Examples: [05:20:01, 19:25:02, 04:05:04]),
(volume_24h:REAL, Examples: [0.0, 46862728.0, 31112234.0]),
(percent_change_1h:REAL, Examples: [0.639231, 0.799273, -0.934763]),
(percent_change_24h:REAL, Examples: [7.63553, 0.920718, 18.558]),
(percent_change_7d:REAL, Examples: [-13.809, -16.7201, 1.64395]),
(circulating_supply:REAL, Examples: [11091325.0, 17164230.0, 18757362.0]),
(total_supply:REAL, Examples: [11091325.0, 17164230.0, 18757362.0]),
(max_supply:REAL, Examples: [21000000.0, 84000000.0, 42000000.0]),
(num_market_pairs:INTEGER, Examples: [7050, 5146, 382])
]

    【Question】
    When is the highest price of Terracoin? when refers to date; the highest price refers to max(price)

    【Evidence】
    when refers to date; the highest price refers to max(price)

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

SQL: SELECT T2.date FROM coins AS T1 INNER JOIN historical AS T2 ON T1.id = T2.coin_id WHERE T1.name = 'Terracoin' ORDER BY T2.price DESC LIMIT 1
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 coinmarketcap
【Schema】
# Table: coins
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(name:TEXT, Examples: [Bitcoin, Litecoin, Namecoin]),
(slug:TEXT, Examples: [bitcoin, litecoin, namecoin]),
(symbol:TEXT, Examples: [BTC, LTC, NMC]),
(status:TEXT, Examples: [active, untracked, inactive]),
(category:TEXT, Examples: [coin, token]),
(description:TEXT),
(subreddit:TEXT, Examples: [bitcoin, litecoin, namecoin]),
(notice:TEXT),
(tags:TEXT),
(tag_names:TEXT),
(website:TEXT),
(platform_id:INTEGER, Examples: [1027, 1765, 1376]),
(date_added:TEXT, Examples: [2013-04-28T00:00:00.000Z]),
(date_launched:TEXT, Examples: [2018-01-16T00:00:00.000Z])
]
# Table: historical
[
(date:DATE, Examples: [2013-04-28]),
(coin_id:INTEGER, Examples: [1, 2, 5]),
(cmc_rank:INTEGER, Examples: [1, 2, 3]),
(market_cap:REAL, Examples: [1488566971.9558687, 74637021.56790735, 7250186.647688276]),
(price:REAL, Examples: [134.210021972656, 4.34840488433838, 0.386524856090546]),
(open:REAL, Examples: [134.44400024414062, 4.366759777069092, 0.3871999979019165]),
(high:REAL, Examples: [147.48800659179688, 4.573599815368652, 0.4247649908065796]),
(low:REAL, Examples: [134.0, 4.225639820098877, 0.37790799140930176]),
(close:REAL, Examples: [144.5399932861328, 4.383900165557861, 0.4088610112667084]),
(time_high:TEXT, Examples: [13:15:01, 13:15:03, 12:45:02]),
(time_low:TEXT, Examples: [05:20:01, 19:25:02, 04:05:04]),
(volume_24h:REAL, Examples: [0.0, 46862728.0, 31112234.0]),
(percent_change_1h:REAL, Examples: [0.639231, 0.799273, -0.934763]),
(percent_change_24h:REAL, Examples: [7.63553, 0.920718, 18.558]),
(percent_change_7d:REAL, Examples: [-13.809, -16.7201, 1.64395]),
(circulating_supply:REAL, Examples: [11091325.0, 17164230.0, 18757362.0]),
(total_supply:REAL, Examples: [11091325.0, 17164230.0, 18757362.0]),
(max_supply:REAL, Examples: [21000000.0, 84000000.0, 42000000.0]),
(num_market_pairs:INTEGER, Examples: [7050, 5146, 382])
]

    【Question】
    How many times was Bytecoin traded in June 2013? in June 2013 refers to year(date) = 2013 AND month(date) = 6

    【Evidence】
    in June 2013 refers to year(date) = 2013 AND month(date) = 6

    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.coin_id) FROM coins AS T1 INNER JOIN historical AS T2 ON T1.id = T2.coin_id WHERE T1.name = 'Bytecoin' AND STRFTIME('%Y-%m', T2.date) = '2013-06'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 coinmarketcap
【Schema】
# Table: coins
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(name:TEXT, Examples: [Bitcoin, Litecoin, Namecoin]),
(slug:TEXT, Examples: [bitcoin, litecoin, namecoin]),
(symbol:TEXT, Examples: [BTC, LTC, NMC]),
(status:TEXT, Examples: [active, untracked, inactive]),
(category:TEXT, Examples: [coin, token]),
(description:TEXT),
(subreddit:TEXT, Examples: [bitcoin, litecoin, namecoin]),
(notice:TEXT),
(tags:TEXT),
(tag_names:TEXT),
(website:TEXT),
(platform_id:INTEGER, Examples: [1027, 1765, 1376]),
(date_added:TEXT, Examples: [2013-04-28T00:00:00.000Z]),
(date_launched:TEXT, Examples: [2018-01-16T00:00:00.000Z])
]
# Table: historical
[
(date:DATE, Examples: [2013-04-28]),
(coin_id:INTEGER, Examples: [1, 2, 5]),
(cmc_rank:INTEGER, Examples: [1, 2, 3]),
(market_cap:REAL, Examples: [1488566971.9558687, 74637021.56790735, 7250186.647688276]),
(price:REAL, Examples: [134.210021972656, 4.34840488433838, 0.386524856090546]),
(open:REAL, Examples: [134.44400024414062, 4.366759777069092, 0.3871999979019165]),
(high:REAL, Examples: [147.48800659179688, 4.573599815368652, 0.4247649908065796]),
(low:REAL, Examples: [134.0, 4.225639820098877, 0.37790799140930176]),
(close:REAL, Examples: [144.5399932861328, 4.383900165557861, 0.4088610112667084]),
(time_high:TEXT, Examples: [13:15:01, 13:15:03, 12:45:02]),
(time_low:TEXT, Examples: [05:20:01, 19:25:02, 04:05:04]),
(volume_24h:REAL, Examples: [0.0, 46862728.0, 31112234.0]),
(percent_change_1h:REAL, Examples: [0.639231, 0.799273, -0.934763]),
(percent_change_24h:REAL, Examples: [7.63553, 0.920718, 18.558]),
(percent_change_7d:REAL, Examples: [-13.809, -16.7201, 1.64395]),
(circulating_supply:REAL, Examples: [11091325.0, 17164230.0, 18757362.0]),
(total_supply:REAL, Examples: [11091325.0, 17164230.0, 18757362.0]),
(max_supply:REAL, Examples: [21000000.0, 84000000.0, 42000000.0]),
(num_market_pairs:INTEGER, Examples: [7050, 5146, 382])
]

    【Question】
    List the names of the coins above the average price on April 28, 2013. average price = divide(sum(price), count(name)); on April 28, 2013 refers to date = '2013-04-28'

    【Evidence】
    average price = divide(sum(price), count(name)); on April 28, 2013 refers to date = '2013-04-28'

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

SQL: SELECT T1.name FROM coins AS T1 INNER JOIN historical AS T2 ON T1.id = T2.coin_id WHERE T2.date = '2018-04-28' AND T2.price > ( SELECT AVG(price) FROM historical WHERE date = '2018-04-28' )
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 coinmarketcap
【Schema】
# Table: coins
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(name:TEXT, Examples: [Bitcoin, Litecoin, Namecoin]),
(slug:TEXT, Examples: [bitcoin, litecoin, namecoin]),
(symbol:TEXT, Examples: [BTC, LTC, NMC]),
(status:TEXT, Examples: [active, untracked, inactive]),
(category:TEXT, Examples: [coin, token]),
(description:TEXT),
(subreddit:TEXT, Examples: [bitcoin, litecoin, namecoin]),
(notice:TEXT),
(tags:TEXT),
(tag_names:TEXT),
(website:TEXT),
(platform_id:INTEGER, Examples: [1027, 1765, 1376]),
(date_added:TEXT, Examples: [2013-04-28T00:00:00.000Z]),
(date_launched:TEXT, Examples: [2018-01-16T00:00:00.000Z])
]
# Table: historical
[
(date:DATE, Examples: [2013-04-28]),
(coin_id:INTEGER, Examples: [1, 2, 5]),
(cmc_rank:INTEGER, Examples: [1, 2, 3]),
(market_cap:REAL, Examples: [1488566971.9558687, 74637021.56790735, 7250186.647688276]),
(price:REAL, Examples: [134.210021972656, 4.34840488433838, 0.386524856090546]),
(open:REAL, Examples: [134.44400024414062, 4.366759777069092, 0.3871999979019165]),
(high:REAL, Examples: [147.48800659179688, 4.573599815368652, 0.4247649908065796]),
(low:REAL, Examples: [134.0, 4.225639820098877, 0.37790799140930176]),
(close:REAL, Examples: [144.5399932861328, 4.383900165557861, 0.4088610112667084]),
(time_high:TEXT, Examples: [13:15:01, 13:15:03, 12:45:02]),
(time_low:TEXT, Examples: [05:20:01, 19:25:02, 04:05:04]),
(volume_24h:REAL, Examples: [0.0, 46862728.0, 31112234.0]),
(percent_change_1h:REAL, Examples: [0.639231, 0.799273, -0.934763]),
(percent_change_24h:REAL, Examples: [7.63553, 0.920718, 18.558]),
(percent_change_7d:REAL, Examples: [-13.809, -16.7201, 1.64395]),
(circulating_supply:REAL, Examples: [11091325.0, 17164230.0, 18757362.0]),
(total_supply:REAL, Examples: [11091325.0, 17164230.0, 18757362.0]),
(max_supply:REAL, Examples: [21000000.0, 84000000.0, 42000000.0]),
(num_market_pairs:INTEGER, Examples: [7050, 5146, 382])
]

    【Question】
    What's the percentage of coins that is higher than the price 1 hour ago in May 29,2013? List the names of these coins. percentage that is higher than the price 1 hour ago refers to percent_change_1h>0; in May 29,2013 refers to date = '2013-05-29'

    【Evidence】
    percentage that is higher than the price 1 hour ago refers to percent_change_1h>0; in May 29,2013 refers to date = '2013-05-29'

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

SQL: SELECT T1.NAME FROM coins AS T1 INNER JOIN historical AS T2 ON T1.ID = T2.coin_id WHERE T2.DATE = '2013-05-29' AND T2.percent_change_1h > 0
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 retail_world
【Schema】
# Table: Orders
[
(OrderID:INTEGER, Primary Key, Examples: [10248, 10249, 10250]),
(CustomerID:INTEGER, Examples: [90, 81, 34]),
(EmployeeID:INTEGER, Examples: [5, 6, 4]),
(OrderDate:DATETIME, Examples: [1996-07-04 00:00:00]),
(ShipperID:INTEGER, Examples: [3, 1, 2])
]
# Table: Suppliers
[
(SupplierID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(SupplierName:TEXT, Examples: [Exotic Liquid]),
(ContactName:TEXT, Examples: [Charlotte Cooper, Shelley Burke, Regina Murphy]),
(Address:TEXT, Examples: [49 Gilbert St., P.O. Box 78934, 707 Oxford Rd.]),
(City:TEXT, Examples: [Londona, New Orleans, Ann Arbor]),
(PostalCode:TEXT, Examples: [EC1 4SD, 70117, 48104]),
(Country:TEXT, Examples: [UK, USA, Japan]),
(Phone:TEXT, Examples: [(171) 555-2222, (100) 555-4822, (313) 555-5735])
]
# Table: Customers
[
(CustomerID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(CustomerName:TEXT, Examples: [Alfreds Futterkiste]),
(ContactName:TEXT, Examples: [Maria Anders, Ana Trujillo, Antonio Moreno]),
(Address:TEXT, Examples: [Obere Str. 57]),
(City:TEXT, Examples: [Berlin, México D.F., London]),
(PostalCode:TEXT, Examples: [12209, 5021, 5023]),
(Country:TEXT, Examples: [Germany, Mexico, UK])
]
# Table: OrderDetails
[
(OrderDetailID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(OrderID:INTEGER, Examples: [10248, 10249, 10250]),
(ProductID:INTEGER, Examples: [11, 42, 72]),
(Quantity:INTEGER, Examples: [12, 10, 5])
]
# Table: Employees
[
(EmployeeID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(LastName:TEXT, Examples: [Davolio, Fuller, Leverling]),
(FirstName:TEXT, Examples: [Nancy, Andrew, Janet]),
(BirthDate:DATE, Examples: [1968-12-08]),
(Photo:TEXT, Examples: [EmpID1.pic, EmpID2.pic, EmpID3.pic]),
(Notes:TEXT)
]
# Table: Shippers
[
(ShipperID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(ShipperName:TEXT, Examples: [Speedy Express, United Package, Federal Shipping]),
(Phone:TEXT, Examples: [(503) 555-9831, (503) 555-3199, (503) 555-9931])
]
# Table: Products
[
(ProductID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(ProductName:TEXT, Examples: [Chais, Chang, Aniseed Syrup]),
(SupplierID:INTEGER, Examples: [1, 2, 3]),
(CategoryID:INTEGER, Examples: [1, 2, 7]),
(Unit:TEXT, Examples: [10 boxes x 20 bags, 24 - 12 oz bottles, 12 - 550 ml bottles]),
(Price:REAL, Examples: [18.0, 19.0, 10.0])
]
# Table: Categories
[
(CategoryID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(CategoryName:TEXT, Examples: [Beverages, Condiments, Confections]),
(Description:TEXT)
]
【Foreign keys】
Orders.EmployeeID=Employees.EmployeeID
Orders.CustomerID=Customers.CustomerID
Orders.ShipperID=Shippers.ShipperID
OrderDetails.OrderID=Orders.OrderID
OrderDetails.ProductID=Products.ProductID
Products.CategoryID=Categories.CategoryID
Products.SupplierID=Suppliers.SupplierID

    【Question】
    How many territories are there?

    【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(TerritoryID) FROM Territories
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 retail_world
【Schema】
# Table: Orders
[
(OrderID:INTEGER, Primary Key, Examples: [10248, 10249, 10250]),
(CustomerID:INTEGER, Examples: [90, 81, 34]),
(EmployeeID:INTEGER, Examples: [5, 6, 4]),
(OrderDate:DATETIME, Examples: [1996-07-04 00:00:00]),
(ShipperID:INTEGER, Examples: [3, 1, 2])
]
# Table: Suppliers
[
(SupplierID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(SupplierName:TEXT, Examples: [Exotic Liquid]),
(ContactName:TEXT, Examples: [Charlotte Cooper, Shelley Burke, Regina Murphy]),
(Address:TEXT, Examples: [49 Gilbert St., P.O. Box 78934, 707 Oxford Rd.]),
(City:TEXT, Examples: [Londona, New Orleans, Ann Arbor]),
(PostalCode:TEXT, Examples: [EC1 4SD, 70117, 48104]),
(Country:TEXT, Examples: [UK, USA, Japan]),
(Phone:TEXT, Examples: [(171) 555-2222, (100) 555-4822, (313) 555-5735])
]
# Table: Customers
[
(CustomerID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(CustomerName:TEXT, Examples: [Alfreds Futterkiste]),
(ContactName:TEXT, Examples: [Maria Anders, Ana Trujillo, Antonio Moreno]),
(Address:TEXT, Examples: [Obere Str. 57]),
(City:TEXT, Examples: [Berlin, México D.F., London]),
(PostalCode:TEXT, Examples: [12209, 5021, 5023]),
(Country:TEXT, Examples: [Germany, Mexico, UK])
]
# Table: OrderDetails
[
(OrderDetailID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(OrderID:INTEGER, Examples: [10248, 10249, 10250]),
(ProductID:INTEGER, Examples: [11, 42, 72]),
(Quantity:INTEGER, Examples: [12, 10, 5])
]
# Table: Employees
[
(EmployeeID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(LastName:TEXT, Examples: [Davolio, Fuller, Leverling]),
(FirstName:TEXT, Examples: [Nancy, Andrew, Janet]),
(BirthDate:DATE, Examples: [1968-12-08]),
(Photo:TEXT, Examples: [EmpID1.pic, EmpID2.pic, EmpID3.pic]),
(Notes:TEXT)
]
# Table: Shippers
[
(ShipperID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(ShipperName:TEXT, Examples: [Speedy Express, United Package, Federal Shipping]),
(Phone:TEXT, Examples: [(503) 555-9831, (503) 555-3199, (503) 555-9931])
]
# Table: Products
[
(ProductID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(ProductName:TEXT, Examples: [Chais, Chang, Aniseed Syrup]),
(SupplierID:INTEGER, Examples: [1, 2, 3]),
(CategoryID:INTEGER, Examples: [1, 2, 7]),
(Unit:TEXT, Examples: [10 boxes x 20 bags, 24 - 12 oz bottles, 12 - 550 ml bottles]),
(Price:REAL, Examples: [18.0, 19.0, 10.0])
]
# Table: Categories
[
(CategoryID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(CategoryName:TEXT, Examples: [Beverages, Condiments, Confections]),
(Description:TEXT)
]
【Foreign keys】
Orders.EmployeeID=Employees.EmployeeID
Orders.CustomerID=Customers.CustomerID
Orders.ShipperID=Shippers.ShipperID
OrderDetails.OrderID=Orders.OrderID
OrderDetails.ProductID=Products.ProductID
Products.CategoryID=Categories.CategoryID
Products.SupplierID=Suppliers.SupplierID

    【Question】
    Provide the territory IDs under employee ID of 7.

    【Evidence】
    

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

SQL: SELECT TerritoryID FROM EmployeeTerritories WHERE EmployeeID = 7
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 retail_world
【Schema】
# Table: Orders
[
(OrderID:INTEGER, Primary Key, Examples: [10248, 10249, 10250]),
(CustomerID:INTEGER, Examples: [90, 81, 34]),
(EmployeeID:INTEGER, Examples: [5, 6, 4]),
(OrderDate:DATETIME, Examples: [1996-07-04 00:00:00]),
(ShipperID:INTEGER, Examples: [3, 1, 2])
]
# Table: Suppliers
[
(SupplierID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(SupplierName:TEXT, Examples: [Exotic Liquid]),
(ContactName:TEXT, Examples: [Charlotte Cooper, Shelley Burke, Regina Murphy]),
(Address:TEXT, Examples: [49 Gilbert St., P.O. Box 78934, 707 Oxford Rd.]),
(City:TEXT, Examples: [Londona, New Orleans, Ann Arbor]),
(PostalCode:TEXT, Examples: [EC1 4SD, 70117, 48104]),
(Country:TEXT, Examples: [UK, USA, Japan]),
(Phone:TEXT, Examples: [(171) 555-2222, (100) 555-4822, (313) 555-5735])
]
# Table: Customers
[
(CustomerID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(CustomerName:TEXT, Examples: [Alfreds Futterkiste]),
(ContactName:TEXT, Examples: [Maria Anders, Ana Trujillo, Antonio Moreno]),
(Address:TEXT, Examples: [Obere Str. 57]),
(City:TEXT, Examples: [Berlin, México D.F., London]),
(PostalCode:TEXT, Examples: [12209, 5021, 5023]),
(Country:TEXT, Examples: [Germany, Mexico, UK])
]
# Table: OrderDetails
[
(OrderDetailID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(OrderID:INTEGER, Examples: [10248, 10249, 10250]),
(ProductID:INTEGER, Examples: [11, 42, 72]),
(Quantity:INTEGER, Examples: [12, 10, 5])
]
# Table: Employees
[
(EmployeeID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(LastName:TEXT, Examples: [Davolio, Fuller, Leverling]),
(FirstName:TEXT, Examples: [Nancy, Andrew, Janet]),
(BirthDate:DATE, Examples: [1968-12-08]),
(Photo:TEXT, Examples: [EmpID1.pic, EmpID2.pic, EmpID3.pic]),
(Notes:TEXT)
]
# Table: Shippers
[
(ShipperID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(ShipperName:TEXT, Examples: [Speedy Express, United Package, Federal Shipping]),
(Phone:TEXT, Examples: [(503) 555-9831, (503) 555-3199, (503) 555-9931])
]
# Table: Products
[
(ProductID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(ProductName:TEXT, Examples: [Chais, Chang, Aniseed Syrup]),
(SupplierID:INTEGER, Examples: [1, 2, 3]),
(CategoryID:INTEGER, Examples: [1, 2, 7]),
(Unit:TEXT, Examples: [10 boxes x 20 bags, 24 - 12 oz bottles, 12 - 550 ml bottles]),
(Price:REAL, Examples: [18.0, 19.0, 10.0])
]
# Table: Categories
[
(CategoryID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(CategoryName:TEXT, Examples: [Beverages, Condiments, Confections]),
(Description:TEXT)
]
【Foreign keys】
Orders.EmployeeID=Employees.EmployeeID
Orders.CustomerID=Customers.CustomerID
Orders.ShipperID=Shippers.ShipperID
OrderDetails.OrderID=Orders.OrderID
OrderDetails.ProductID=Products.ProductID
Products.CategoryID=Categories.CategoryID
Products.SupplierID=Suppliers.SupplierID

    【Question】
    What is the title of Michael Suyama?

    【Evidence】
    

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

SQL: SELECT Title FROM Employees WHERE FirstName = 'Michael' AND LastName = 'Suyama'