Table:
30 June 2019	30 June 2018	Change

$’000	$’000	%

Net profit/(loss) after tax	(9,819)	6,639	(248%)

Add: finance costs	54,897	25,803	113%

Less: interest income	(8,220)	(5,778)	42%

Add/(less): income tax expense/(benefit)	(6,254)	4,252	(247%)

Add: depreciation and amortisation	48,442	33,038	47%

EBITDA	79,046	63,954	24%

Less: gain on extinguishment of B1 lease	(1,068)	-

Less: gain on extinguishment of APDC leases	(1,291)	-

Less: distribution income	(1,344)	(3,191)	(58%)

Add: APDC transaction costs	5,459	1,812	201%

Add: landholder duty on acquisition of APDC properties	3,498	-

Add: Singapore and Japan costs	823	-

Underlying EBITDA	85,123	62,575	36%

row 6,
column 1,
Extract the contents of cells in the above rows or columns, identified by row or column indices. Show the cells in each row or column in the JSON format {"row_id/column_id":"<row or column index>", "cell_list":"<a list of cells in this row/column>"}. For example, {"row_id":"3", "cell_list": ["A", "B", "C"]}.

The cell values of target rows or columns are as follows:
For row 6: {"row_id": "6", "cell_list": ['Add/(less): income tax expense/(benefit)', '(6,254)', '4,252', '(247%)']}
For column 1: {"column_id": "1", "cell_list": ['', '', 'Net profit/(loss) after tax', 'Add: finance costs', 'Less: interest income', 'Add/(less): income tax expense/(benefit)', 'Add: depreciation and amortisation', 'EBITDA', 'Less: gain on extinguishment of B1 lease', 'Less: gain on extinguishment of APDC leases', 'Less: distribution income', 'Add: APDC transaction costs', 'Add: landholder duty on acquisition of APDC properties', 'Add: Singapore and Japan costs', 'Underlying EBITDA']}