You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 public_review_platform
【Schema】
# Table: Days
[
(day_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(day_of_week:TEXT, Examples: [Sunday, Monday, Tuesday])
]
# Table: Users
[
(user_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(user_yelping_since_year:INTEGER, Examples: [2012, 2010, 2009]),
(user_average_stars:TEXT, Examples: [4.0, 2.5, 4.5]),
(user_votes_funny:TEXT, Examples: [Low, None, Uber]),
(user_votes_useful:TEXT, Examples: [Low, Medium, Uber]),
(user_votes_cool:TEXT, Examples: [Low, Uber, None]),
(user_review_count:TEXT, Examples: [Medium, High, Low]),
(user_fans:TEXT, Examples: [Low, None, Medium])
]
# Table: Elite
[
(user_id:INTEGER, Primary Key, Examples: [3, 19, 33]),
(year_id:INTEGER, Primary Key, Examples: [2010, 2011, 2012])
]
# Table: Business_Attributes
[
(attribute_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(business_id:INTEGER, Primary Key, Examples: [2, 3, 13]),
(attribute_value:TEXT, Examples: [none, full_bar, beer_and_wine])
]
# Table: Compliments
[
(compliment_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(compliment_type:TEXT, Examples: [photos, cool, hot])
]
# Table: Business
[
(business_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(active:TEXT, Examples: [true, false]),
(city:TEXT, Examples: [Phoenix, Scottsdale, Glendale]),
(state:TEXT, Examples: [AZ, SC, CA]),
(stars:REAL, Examples: [3.0, 4.5, 4.0]),
(review_count:TEXT, Examples: [Low, Medium, High])
]
# Table: Business_Categories
[
(business_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(category_id:INTEGER, Primary Key, Examples: [8, 143, 18])
]
# Table: Reviews
[
(business_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(user_id:INTEGER, Primary Key, Examples: [36129, 40299, 59125]),
(review_stars:INTEGER, Examples: [2, 1, 5]),
(review_votes_funny:TEXT, Examples: [None, Low, Medium]),
(review_votes_useful:TEXT, Examples: [None, Low, Medium]),
(review_votes_cool:TEXT, Examples: [None, Low, Medium]),
(review_length:TEXT, Examples: [Medium, Short, Long])
]
# Table: Business_Hours
[
(business_id:INTEGER, Primary Key, Examples: [2, 3, 4]),
(day_id:INTEGER, Primary Key, Examples: [2, 3, 4]),
(opening_time:TEXT, Examples: [11AM, 12PM, 10AM]),
(closing_time:TEXT, Examples: [8PM, 9PM, 6PM])
]
# Table: Years
[
(year_id:INTEGER, Primary Key, Examples: [2005, 2006, 2007]),
(actual_year:INTEGER, Examples: [2005, 2006, 2007])
]
# Table: Attributes
[
(attribute_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(attribute_name:TEXT, Examples: [Alcohol, Waiter Service, Delivery])
]
# Table: Users_Compliments
[
(compliment_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(user_id:INTEGER, Primary Key, Examples: [3, 19, 45]),
(number_of_compliments:TEXT, Examples: [Medium, Low, High])
]
# Table: Checkins
[
(business_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(day_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(label_time_0:TEXT, Examples: [None, Low, Medium]),
(label_time_1:TEXT, Examples: [None, Low, Medium]),
(label_time_2:TEXT, Examples: [None, Low, Medium]),
(label_time_3:TEXT, Examples: [None, Low, Medium]),
(label_time_4:TEXT, Examples: [None, Low, Medium]),
(label_time_5:TEXT, Examples: [None, Low, Medium]),
(label_time_6:TEXT, Examples: [None, Low, Medium]),
(label_time_7:TEXT, Examples: [None, Low, Medium]),
(label_time_8:TEXT, Examples: [None, Low, Medium]),
(label_time_9:TEXT, Examples: [Low, None, Medium]),
(label_time_10:TEXT, Examples: [None, Low, Medium]),
(label_time_11:TEXT, Examples: [Low, None, Medium]),
(label_time_12:TEXT, Examples: [None, Low, Medium]),
(label_time_13:TEXT, Examples: [None, Low, Medium]),
(label_time_14:TEXT, Examples: [None, Low, Medium]),
(label_time_15:TEXT, Examples: [None, Low, Medium]),
(label_time_16:TEXT, Examples: [None, Low, Medium]),
(label_time_17:TEXT, Examples: [Low, None, Medium]),
(label_time_18:TEXT, Examples: [None, Low, Medium]),
(label_time_19:TEXT, Examples: [None, Low, Medium]),
(label_time_20:TEXT, Examples: [None, Low, Medium]),
(label_time_21:TEXT, Examples: [None, Low, Medium]),
(label_time_22:TEXT, Examples: [None, Low, Medium]),
(label_time_23:TEXT, Examples: [None, Low, Medium])
]
# Table: Tips
[
(business_id:INTEGER, Primary Key, Examples: [2, 3, 6]),
(user_id:INTEGER, Primary Key, Examples: [12490, 16328, 19191]),
(likes:INTEGER, Examples: [0, 1, 2]),
(tip_length:TEXT, Examples: [Medium, Short, Long])
]
# Table: Categories
[
(category_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(category_name:TEXT, Examples: [Active Life, Arts & Entertainment, Stadiums & Arenas])
]
【Foreign keys】
Elite.year_id=Years.year_id
Elite.user_id=Users.user_id
Business_Attributes.business_id=Business.business_id
Business_Attributes.attribute_id=Attributes.attribute_id
Business_Categories.category_id=Categories.category_id
Business_Categories.business_id=Business.business_id
Reviews.user_id=Users.user_id
Reviews.business_id=Business.business_id
Business_Hours.day_id=Days.day_id
Business_Hours.business_id=Business.business_id
Users_Compliments.user_id=Users.user_id
Users_Compliments.compliment_id=Compliments.compliment_id
Checkins.day_id=Days.day_id
Checkins.business_id=Business.business_id
Tips.user_id=Users.user_id
Tips.business_id=Business.business_id

    【Question】
    For the Yelp business in "Tempe" city which got "3.5" stars and review count as "Uber", how many "long" reviews did it get? "Tempe" is the name of city; long review refers to review_length = 'Long'

    【Evidence】
    "Tempe" is the name of city; long review refers to review_length = 'Long'

    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.review_length) FROM Business AS T1 INNER JOIN Reviews AS T2 ON T1.business_id = T2.business_id WHERE T1.city = 'Tempe' AND T1.stars = '3.5' AND T1.review_count = 'Uber' AND T2.review_length = 'Long'