Table:
outcome	date	surface	opponent	score

winner	25 september 2000	clay	diego nargiso	7 - 6 (16 - 14) , 6 - 1

runner - up	11 february 2002	hard (i)	lars burgsmüller	3 - 6 , 3 - 6

runner - up	3 march 2003	hard (i)	karol kučera	6 - 7 (4 - 7) , 4 - 6

runner - up	15 january 2005	hard	fernando gonzález	4 - 6 , 2 - 6

winner	1 may 2006	clay	kristof vliegen	6 - 4 , 6 - 2

runner - up	24 september 2007	hard	richard gasquet	3 - 6 , 4 - 6

runner - up	25 october 2009	hard (i)	marcos baghdatis	1 - 6 , 5 - 7

runner - up	11 july 2010	grass	mardy fish	7 - 5 , 3 - 6 , 4 - 6

runner - up	10 july 2011	grass	john isner	3 - 6 , 6 - 7 (6 - 8)

runner - up	14 january 2012	hard	david ferrer	3 - 6 , 4 - 6

Given a table image and a set of target cells, your task is to identify their positions. Represent each cell's location as JSON in the format {'value': '<cell value>', 'location': (row number, column number)}, with both row and column number begin from 1.
Refer to the values below:
1. 'Rosa estaràs ferragut, spain-mip-europaparlament-by-leila-paul-1. jpg';
2. '6 - 4 , 6 - 2';
3. '15 january 2005';
4. '21 october 1965';
5. '1 - 6 , 5 - 7';

Use 'DOES NOT EXIST' as the location for a non-existing cell in the table. 

The coordinates of target cells are listed below.
1. {'value': 'Rosa estaràs ferragut, spain-mip-europaparlament-by-leila-paul-1. jpg', 'location': 'DOES NOT EXIST'}
2. {'value': '6 - 4 , 6 - 2', 'location': (6, 5)}
3. {'value': '15 january 2005', 'location': (5, 2)}
4. {'value': '21 october 1965', 'location': 'DOES NOT EXIST'}
5. {'value': '1 - 6 , 5 - 7', 'location': (8, 5)}