Table:
tournament	2007	2008	2009	2010	2011

grand slam tournaments	grand slam tournaments	grand slam tournaments	grand slam tournaments	grand slam tournaments	grand slam tournaments

australian open	a	1r	1r	1r	1r

french open	a	3r	3r	2r	2r

wimbledon	2r	1r	2r	1r	1r

us open	2r	2r	1r	1r	1r

win - loss	2 - 2	3 - 4	3 - 4	1 - 4	1 - 4

olympic games	olympic games	olympic games	olympic games	olympic games	olympic games

summer olympics	nh	1r	not held	not held	not held

year - end championship	year - end championship	year - end championship	year - end championship	year - end championship	year - end championship

wta tour championships	a	a	a	a	a

wta premier mandatory tournaments	wta premier mandatory tournaments	wta premier mandatory tournaments	wta premier mandatory tournaments	wta premier mandatory tournaments	wta premier mandatory tournaments

indian wells	a	a	2r	2r	1r

miami	a	1r	1r	1r	1r

madrid	not held	not held	lq	2r	a

beijing	1r	lq	1r	2r	lq

wta premier 5 tournaments	wta premier 5 tournaments	wta premier 5 tournaments	wta premier 5 tournaments	wta premier 5 tournaments	wta premier 5 tournaments

dubai	not tieri	not tieri	1r	3r	a

rome	a	2r	a	1r	lq

cincinnati	qf	a	2r	2r	lq

montréal / toronto	a	a	a	1r	lq

tokyo	a	a	a	2r	a

year end ranking	49	49	52	74	114

Based on the table image, extract the cell contents located in row 21. Output the cell values in a row as JSON in the format {"row_id":"<row index>", "cell_list":"<a list of cells in this row>"}, e.g., {"row_id":"3", "cell_list": ["123.89", "News gathering", "selected tools"]}.

The target cell values of row 21: {"row_id": "21", "cell_list": ['montréal / toronto', 'a', 'a', 'a', '1r', 'lq']}