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 M0 marry M5 , M6 , and M7 , influence M1 , and influence M2 , M3 , and M4
Example Output: SELECT count(*) WHERE {
FILTER ( M0 != M5 ) .
FILTER ( M0 != M6 ) .
FILTER ( M0 != M7 ) .
M0 ns:influence.influence_node.influenced M1 .
M0 ns:influence.influence_node.influenced M2 .
M0 ns:influence.influence_node.influenced M3 .
M0 ns:influence.influence_node.influenced M4 .
M0 ns:people.person.spouse_s/ns:people.marriage.spouse|ns:fictional_universe.fictional_character.married_to/ns:fictional_universe.marriage_of_fictional_characters.spouses M5 .
M0 ns:people.person.spouse_s/ns:people.marriage.spouse|ns:fictional_universe.fictional_character.married_to/ns:fictional_universe.marriage_of_fictional_characters.spouses M6 .
M0 ns:people.person.spouse_s/ns:people.marriage.spouse|ns:fictional_universe.fictional_character.married_to/ns:fictional_universe.marriage_of_fictional_characters.spouses M7
}

Example Input: Did M1 influence M2 , M3 , and M4 , marry a person , and influence M5 , M6 , and M7
Example Output: SELECT count(*) WHERE {
?x0 a ns:people.person .
FILTER ( M1 != ?x0 ) .
M1 ns:influence.influence_node.influenced M2 .
M1 ns:influence.influence_node.influenced M3 .
M1 ns:influence.influence_node.influenced M4 .
M1 ns:influence.influence_node.influenced M5 .
M1 ns:influence.influence_node.influenced M6 .
M1 ns:influence.influence_node.influenced M7 .
M1 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 M3 star a male Chinese film editor
Example Output:
SELECT count(*) WHERE {
?x0 a ns:film.editor .
?x0 ns:people.person.gender ns:m.05zppz .
?x0 ns:people.person.nationality ns:m.0d05w3 .
M3 ns:film.film.starring/ns:film.performance.actor ?x0
}