Generate SQL given the question, table, passages, image captions to answer the question correctly.
If question-relevant column(s) contents are not suitable for SQL comparisons or calculations, map it to a new column with clean content by a new grammar QA("map@").
If mapping to a new column still can not answer the question with valid SQL, turn to an end-to-end solution by a new grammar QA("ans@"). This grammar aims to solve all the rest of complex questions or tables or passages or image captions.

CREATE TABLE NAME_1 NAME_2 (Electoral history)(
	row_id int,
	year int,
	office text,
	election text,
	filledcolumnname real,
	subject text,
	party text,
	votes text,
	% text,
	filledcolumnname_2 real,
	opponent text,
	party_2 text,
	votes_2 text,
	%_2 text)
/*
3 example rows:
SELECT * FROM w LIMIT 3;
row_id	year	office	election	filledcolumnname	subject	party	votes	%	filledcolumnname_2	opponent	party_2	votes_2	%_2
0	1994	baltimore county executive	general	nan	NAME_1 NAME_2	democratic	n/a	n/a	nan	n/a	n/a	n/a	n/a
1	1998	baltimore county executive	general	nan	NAME_1 NAME_2	democratic	166482	70.47	NAME_3. bishop	republican	69449	29.4
2	2002	none	general	nan	NAME_1 NAME_2	democratic	105718	54.16	nan	NAME_4 bentley	republican	88954	45.57
*/
Q: What year was NAME_5 NAME_6 the opponent of NAME_7?
NeuralSQL: SELECT year FROM w WHERE opponent = 'NAME_5 NAME_6'


CREATE TABLE Virtual Console (Titles)(
	row_id int,
	system text,
	japan int,
	[[list of virtual console  There should be exactly 7 paragraphs separated by the markdown divider: ***.
user