For the given English description, write an SQL command such that it accomplishes every step. An SQL query works by selecting data from a table where certain conditions apply. A table contains columns where every row in that table must have a value for each column. Every table has a primary key that uniquely identifies each row, usually an id. To choose which columns are returned you specify that after the "SELECT" statement. Next, you use a "FROM" statement to specify what tables you want to select the data from. When you specify a table you can rename it with the "AS" statement. You can reference that table by whatever name follows the "AS" statement. If you want to select data from multiple tables you need to use the "JOIN" statement. This will join the tables together by pairing a row in one table with every row in the other table (Cartesian Product). To limit the number of rows returned you should use the "ON" statement. This will only return rows where the condition specified after the statement is true, this is usually an equals operator with primary keys. You can also use the "WHERE" statement to specify that only rows with column values statisfying a certain condition, should be returned. The "GROUP BY" statement will group rows together that have equal column values for whatever columns follows the statement. The "HAVING" statement will return groups that statisfy whatever condition follows the statement. Any column(s) being returned from grouped rows must either be an aggregate function, (AVG, MAX, COUNT, SUM, ...) of a column, or the column(s) that the data was grouped by. To sort the returned data you can use the "ORDER BY" command which will order the data by whatever aggregate function or column follows the statement. The "DESC" statement will sort in descending order and the "ASC" statement will sort in ascending order. Finally, you can use the "LIMIT" statement to return a certain number of rows. When "*" is used in an SQL statement every column is returned. For example, SELECT * FROM table WHERE attribute = 1, will select every column from rows with the attribute column equal to 1.

Example Input: Did M4 marry a female Italian film producer whose child produced M3
Example Output: SELECT count(*) WHERE {
?x0 a ns:film.producer .
?x0 ns:people.person.children|ns:fictional_universe.fictional_character.children|ns:organization.organization.child/ns:organization.organization_relationship.child ?x1 .
?x0 ns:people.person.gender ns:m.02zsn .
?x0 ns:people.person.nationality ns:m.03rjj .
?x1 ns:film.producer.film|ns:film.production_company.films M3 .
FILTER ( M4 != ?x0 ) .
M4 ns:people.person.spouse_s/ns:people.marriage.spouse|ns:fictional_universe.fictional_character.married_to/ns:fictional_universe.marriage_of_fictional_characters.spouses ?x0
}

Example Input: Did M0 's director , executive producer , producer , and art director executive produce M1 , M2 , and M3
Example Output: SELECT count(*) WHERE {
?x0 ns:film.director.film M0 .
?x0 ns:film.film_art_director.films_art_directed M0 .
?x0 ns:film.producer.films_executive_produced M0 .
?x0 ns:film.producer.films_executive_produced M1 .
?x0 ns:film.producer.films_executive_produced M2 .
?x0 ns:film.producer.films_executive_produced M3 .
?x0 ns:film.producer.film|ns:film.production_company.films M0
}

Example Input: Did M1 's employee and founder influence a screenwriter , influence M0 , and marry M2
Example Output:
SELECT count(*) WHERE {
?x0 ns:influence.influence_node.influenced ?x1 .
?x0 ns:influence.influence_node.influenced M0 .
?x0 ns:organization.organization_founder.organizations_founded M1 .
?x0 ns:people.person.employment_history/ns:business.employment_tenure.company M1 .
?x0 ns:people.person.spouse_s/ns:people.marriage.spouse|ns:fictional_universe.fictional_character.married_to/ns:fictional_universe.marriage_of_fictional_characters.spouses M2 .
?x1 a ns:film.writer .
FILTER ( ?x0 != M2 )
}