Task: Table-QA (source dataset: FinQA)

Task: 
You are given a table containing structured data and a natural language question referring to the table. Your goal is to analyze the table and provide an accurate and concise answer based on the given data.

Instructions:
1. Understand the Table: Examine the structure, headers, and data in the table. Identify relevant columns and rows related to the question.
2. Interpret the Question: Determine whether the question requires direct retrieval, aggregation, comparison, sorting, filtering, or inference.
3. Extract the Answer: Use logical reasoning and numerical operations (if necessary) to derive the correct response from the table.
4. Format the Answer: No explanation, return the answer in a structured JSON format: {"answer": <answer>}. If the question cannot be answered due to missing or ambiguous data, return a JSON response with {"answer": null}.

Table:
| in millions of dollars                                       | 2009             | 2008               | 2007               | % (  % ) change 2009 vs . 2008   | % (  % ) change 2008 vs . 2007   |
|:-------------------------------------------------------------|:-----------------|:-------------------|:-------------------|:---------------------------------|:---------------------------------|
| net interest revenue                                         | $ 3173           | $ 3332             | $ 2723             | ( 5 ) % (  % )                   | 22% ( 22 % )                     |
| non-interest revenue                                         | -6855 ( 6855 )   | -42906 ( 42906 )   | -20619 ( 20619 )   | 84                               | nm                               |
| revenues net of interest expense                             | $ -3682 ( 3682 ) | $ -39574 ( 39574 ) | $ -17896 ( 17896 ) | 91% ( 91 % )                     | nm                               |
| total operating expenses                                     | $ 896            | $ 988              | $ 1070             | ( 9 ) % (  % )                   | ( 8 ) % (  % )                   |
| net credit losses                                            | $ 5420           | $ 909              | $ 436              | nm                               | nm                               |
| provision for unfunded lending commitments                   | 111              | -172 ( 172 )       | 71                 | nm                               | nm                               |
| credit reserve builds/ ( release )                           | -483 ( 483 )     | 2844               | 378                | nm                               | nm                               |
| provisions for credit losses and for benefits and claims     | $ 5048           | $ 3581             | $ 885              | 41% ( 41 % )                     | nm                               |
| ( loss ) from continuing operations before taxes             | $ -9626 ( 9626 ) | $ -44143 ( 44143 ) | $ -19851 ( 19851 ) | 78% ( 78 % )                     | nm                               |
| income taxes ( benefits )                                    | -4323 ( 4323 )   | -17149 ( 17149 )   | -7740 ( 7740 )     | 75                               | nm                               |
| ( loss ) from continuing operations                          | $ -5303 ( 5303 ) | $ -26994 ( 26994 ) | $ -12111 ( 12111 ) | 80% ( 80 % )                     | nm                               |
| net income ( loss ) attributable to noncontrolling interests | -17 ( 17 )       | -205 ( 205 )       | 149                | 92                               | nm                               |
| net ( loss )                                                 | $ -5286 ( 5286 ) | $ -26789 ( 26789 ) | $ -12260 ( 12260 ) | 80% ( 80 % )                     | nm                               |
| eop assets ( in billions of dollars )                        | $ 154            | $ 241              | $ 351              | ( 36 ) % (  % )                  | ( 31 ) % (  % )                  |

Question:
what percent of net interest revenue where total operating expenses in 2009?


pre_text: special asset pool special asset pool ( sap ) , which constituted approximately 28% ( 28 % ) of citi holdings by assets as of december 31 , 2009 , is a portfolio of securities , loans and other assets that citigroup intends to actively reduce over time through asset sales and portfolio run-off .
at december 31 , 2009 , sap had $ 154 billion of assets .
sap assets have declined by $ 197 billion or 56% ( 56 % ) from peak levels in 2007 reflecting cumulative write-downs , asset sales and portfolio run-off .
assets have been reduced by $ 87 billion from year-ago levels .
approximately 60% ( 60 % ) of sap assets are now accounted for on an accrual basis , which has helped reduce income volatility .
in millions of dollars 2009 2008 2007 % (  % ) change 2009 vs .
2008 % (  % ) change 2008 vs .
2007 .
post_text: nm not meaningful 2009 vs .
2008 revenues , net of interest expense increased $ 35.9 billion in 2009 , primarily due to the absence of significant negative revenue marks occurring in the prior year .
total negative marks were $ 1.9 billion in 2009 as compared to $ 38.1 billion in 2008 , as described in more detail below .
revenue in the current year included a positive $ 1.3 billion cva on derivative positions , excluding monoline insurers , and positive marks of $ 0.8 billion on subprime-related direct exposures .
these positive revenues were partially offset by negative revenues of $ 1.5 billion on alt-a mortgages , $ 1.3 billion of write-downs on commercial real estate , and a negative $ 1.6 billion cva on the monoline insurers and fair value option liabilities .
revenue was also affected by negative marks on private equity positions and write-downs on highly leveraged finance commitments .
operating expenses decreased 9% ( 9 % ) in 2009 , mainly driven by lower compensation and lower volumes and transaction expenses , partially offset by costs associated with the u.s .
government loss-sharing agreement , which citi exited in the fourth quarter of 2009 .
provisions for credit losses and for benefits and claims increased $ 1.5 billion , primarily driven by $ 4.5 billion in increased net credit losses , partially offset by a lower reserve build of $ 3.0 billion .
assets declined 36% ( 36 % ) versus the prior year , primarily driven by amortization and prepayments , sales , marks and charge-offs .
asset sales during the fourth quarter of 2009 ( $ 10 billion ) were executed at or above citi 2019s marks generating $ 800 million in pretax gains for the quarter .
2008 vs .
2007 revenues , net of interest expense decreased $ 21.7 billion , primarily due to negative net revenue marks .
revenue included $ 14.3 billion of write- downs on subprime-related direct exposures and a negative $ 6.8 billion cva related to the monoline insurers and derivative positions .
revenue was also negatively affected by write-downs on highly leveraged finance commitments , alt-a mortgage revenue , write-downs on structured investment vehicles and commercial real estate , and mark-to-market on auction rate securities .
total negative marks were $ 38.1 billion in 2008 as compared to $ 20.2 billion in 2007 , which are described in more detail below .
operating expenses decreased 8% ( 8 % ) , mainly driven by lower compensation and transaction expenses .
provisions for credit losses and for benefits and claims increased $ 2.7 billion , primarily due to a $ 2.2 billion increase in the reserve build and an increase in net credit losses of $ 0.5 billion .
assets declined 31% ( 31 % ) versus the prior year , primarily driven by amortization and prepayments , sales , and marks and charge-offs. .
label: 0.28238
qa: answer: 28%
explanation: looking to see if the cost are outweighed by the payment stream prior to other write offs .
ann_table_rows: 1
4
steps: op: divide1-1
arg1: 896
arg2: 3173
res: 28%
program: divide(896, 3173)
gold_inds: table_1: in millions of dollars the net interest revenue of 2009 is $ 3173 ; the net interest revenue of 2008 is $ 3332 ; the net interest revenue of 2007 is $ 2723 ; the net interest revenue of % ( % ) change 2009 vs . 2008 is ( 5 ) % ( % ) ; the net interest revenue of % ( % ) change 2008 vs . 2007 is 22% ( 22 % ) ;
table_4: in millions of dollars the total operating expenses of 2009 is $ 896 ; the total operating expenses of 2008 is $ 988 ; the total operating expenses of 2007 is $ 1070 ; the total operating expenses of % ( % ) change 2009 vs . 2008 is ( 9 ) % ( % ) ; the total operating expenses of % ( % ) change 2008 vs . 2007 is ( 8 ) % ( % ) ;
exe_ans: 0.28238
tfidftopn: text_24: operating expenses decreased 8% ( 8 % ) , mainly driven by lower compensation and transaction expenses .
program_re: divide(896, 3173)
model_input: table_1
in millions of dollars the net interest revenue of 2009 is $ 3173 ; the net interest revenue of 2008 is $ 3332 ; the net interest revenue of 2007 is $ 2723 ; the net interest revenue of % ( % ) change 2009 vs . 2008 is ( 5 ) % ( % ) ; the net interest revenue of % ( % ) change 2008 vs . 2007 is 22% ( 22 % ) ;
table_3
in millions of dollars the revenues net of interest expense of 2009 is $ -3682 ( 3682 ) ; the revenues net of interest expense of 2008 is $ -39574 ( 39574 ) ; the revenues net of interest expense of 2007 is $ -17896 ( 17896 ) ; the revenues net of interest expense of % ( % ) change 2009 vs . 2008 is 91% ( 91 % ) ; the revenues net of interest expense of % ( % ) change 2008 vs . 2007 is nm ;
table_4
in millions of dollars the total operating expenses of 2009 is $ 896 ; the total operating expenses of 2008 is $ 988 ; the total operating expenses of 2007 is $ 1070 ; the total operating expenses of % ( % ) change 2009 vs . 2008 is ( 9 ) % ( % ) ; the total operating expenses of % ( % ) change 2008 vs . 2007 is ( 8 ) % ( % ) ;