MMTU-benchmark/MMTU huggingface dataset:
Task: Table-QA (source dataset: TableBench)

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:
|   year |   indians admitted |   pakistanis admitted |   sri lankans admitted |   bangladeshis admitted |   nepalis admitted |
|-------:|-------------------:|----------------------:|-----------------------:|------------------------:|-------------------:|
|   2000 |              26122 |                 14201 |                   5849 |                    2715 |                247 |
|   2001 |              27901 |                 15353 |                   5520 |                    3393 |                273 |
|   2002 |              28838 |                 14173 |                   4968 |                    2615 |                418 |
|   2003 |              24595 |                 12351 |                   4448 |                    1896 |                440 |
|   2004 |              25573 |                 12793 |                   4134 |                    3374 |                594 |
|   2005 |              22141 |                 13575 |                   4690 |                    3940 |                714 |
|   2006 |              30746 |                 12329 |                   4490 |                    3838 |                640 |
|   2007 |              26047 |                  9545 |                   3934 |                    2735 |                564 |
|   2008 |              24548 |                  8051 |                   4508 |                    2716 |                639 |
|   2009 |              26117 |                  6213 |                   4270 |                    4270 |                627 |
|   2010 |              30252 |                  4986 |                   4181 |                    4364 |               1502 |
|   2011 |              24965 |                  6073 |                   3104 |                    2449 |               1249 |
|   2012 |              28943 |                  9931 |                   3152 |                    2449 |               1311 |

Question:
What is the total number of Indians and Pakistanis admitted in the year 2005?


id: e367ed190aaf27d2df92a69e9b72a409
qtype: NumericalReasoning
label: 35716
Task: Table-QA (source dataset: TableBench)

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:
| date                          |   total usaaf |   tot officers |   tot enlisted |   overseas |   officers o / s |   enlisted o / s |
|:------------------------------|--------------:|---------------:|---------------:|-----------:|-----------------:|-----------------:|
| 31 july 1939                  |         24724 |           2636 |          22088 |       3991 |              272 |             3719 |
| 31 december 1939              |         43118 |           3006 |          40112 |       7007 |              351 |             6656 |
| 31 december 1940              |        101227 |           6437 |          94790 |      16070 |              612 |            15458 |
| 31 december 1941              |        354161 |          24521 |         329640 |      25884 |             2479 |            23405 |
| 31 december 1942              |       1597049 |         127267 |        1469782 |     242021 |            26792 |           215229 |
| 31 december 1943              |       2373882 |         274347 |        2099535 |     735666 |            81072 |           654594 |
| 31 march 1944 (peak size)     |       2411294 |         306889 |        2104405 |     906335 |           104864 |           801471 |
| 31 december 1944              |       2359456 |         375973 |        1983483 |    1164136 |           153545 |          1010591 |
| 30 april 1945 (peak overseas) |       2329534 |         388278 |        1941256 |    1224006 |           163886 |          1060120 |

Question:
In the context of USAAF personnel statistics, the "Overseas Rate" is calculated as the total number of personnel overseas divided by the total USAAF personnel, multiplied by 100, indicating the percentage of personnel deployed overseas. On which date did the USAAF have the highest Overseas Rate?


id: 894156fdcc6661fd7ec5038fb090c32a
qtype: NumericalReasoning
label: 30 April 1945
Task: Table-QA (source dataset: TableBench)

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:
| year   |   matches |   wins |   losses |   no result |   tied | success rate   |
|:-------|----------:|-------:|---------:|------------:|-------:|:---------------|
| 2008   |        16 |      9 |        7 |           0 |      0 | 56.25%         |
| 2009   |        15 |      8 |        6 |           1 |      0 | 53.33%         |
| 2010   |        16 |      9 |        7 |           0 |      0 | 56.25%         |
| 2011   |        16 |     11 |        5 |           0 |      0 | 68.75%         |
| 2012   |        19 |     19 |       11 |           8 |      0 | 52.63%         |
| 2013   |        18 |     12 |        6 |           0 |      0 | 66.67%         |
| total  |        99 |     59 |       39 |           1 |      0 | 60.2%          |

Question:
In which year did the team achieve the highest success rate?


id: 682533d22442892ff958f52e5523cead
qtype: NumericalReasoning
label: 2011
Task: Table-QA (source dataset: TableBench)

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:
|   rank | nation               |   gold |   silver |   bronze |   total |
|-------:|:---------------------|-------:|---------:|---------:|--------:|
|      1 | cuba                 |      7 |        4 |        3 |      14 |
|      2 | venezuela            |      6 |        6 |        4 |      16 |
|      3 | jamaica              |      5 |        3 |        5 |      13 |
|      4 | mexico               |      3 |        4 |        5 |      12 |
|      5 | colombia             |      3 |        0 |        4 |       7 |
|      6 | puerto rico          |      1 |        4 |        4 |       9 |
|      7 | netherlands antilles |      1 |        1 |        0 |       2 |
|      8 | bahamas              |      1 |        0 |        1 |       2 |
|      9 | guyana               |      1 |        1 |        0 |       2 |
|     10 | guatemala            |      1 |        0 |        0 |       1 |
|     11 | panama               |      0 |        3 |        1 |       4 |
|     12 | trinidad and tobago  |      0 |        2 |        2 |       4 |
|     13 | barbados             |      0 |        1 |        0 |       1 |

Question:
Which nation ranked 3rd in the competition ?


id: b991baa4ea3f9da3acf4bea043fd5b4d
qtype: FactChecking
label: jamaica
Task: Table-QA (source dataset: TableBench)

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:
|   Rank | Death toll   |   Magnitude | Location                           |   Depth (km) | Date        |
|-------:|:-------------|------------:|:-----------------------------------|-------------:|:------------|
|      1 | 60,000       |         7.5 | Pakistan Baluchistan, Pakistan     |           25 | May 30      |
|      2 | 3,276        |         7   | Taiwan Taichung City, Taiwan       |           15 | April 20    |
|      3 | 2,746        |         6.5 | Taiwan Miaoli County, Taiwan       |           30 | July 16     |
|      4 | 690          |         6.4 | Iran Mazandaran Province, Iran     |           15 | April 11    |
|      5 | 540          |         6   | Turkey Agri Province, Turkey       |           35 | May 1       |
|      6 | 100          |         6   | China Sichuan Province, China      |           35 | December 18 |
|      7 | 60           |         6   | Iran Mazandaran Province, Iran     |           35 | March 5     |
|      8 | 51           |         6.8 | Greece southern Aegean Sea, Greece |           80 | February 25 |

Question:
How many earthquakes have a magnitude of 6.0 or higher?


id: 01cc27d3caf4e8c915554b92786ff40f
qtype: NumericalReasoning
label: 8
Task: Table-QA (source dataset: TableBench)

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:
| country        |   preliminary |   interview |   swimsuit |   evening gown |   average |
|:---------------|--------------:|------------:|-----------:|---------------:|----------:|
| california     |         8.435 |       8.861 |      9.211 |          9.2   |     9.09  |
| texas          |         8.671 |       9.322 |      9.177 |          9.3   |     9.266 |
| south carolina |         8.075 |       8.733 |      8.65  |          8.744 |     8.709 |
| louisiana      |         8.147 |       8.644 |      8.8   |          8.9   |     8.781 |
| north dakota   |         7.949 |       8.955 |      8.3   |          8.422 |     8.559 |
| oklahoma       |         7.844 |       8.688 |      8.266 |          8.566 |     8.506 |
| nevada         |         8.147 |       8.011 |      8.866 |          8.322 |     8.399 |
| washington     |         8.207 |       7.977 |      8.577 |          8.633 |     8.395 |
| michigan       |         7.864 |       8.525 |      8.366 |          8.272 |     8.387 |
| pennsylvania   |         8.035 |       8.166 |      8.555 |          8.377 |     8.366 |
| georgia        |         7.903 |       7.655 |      8.588 |          8.755 |     8.332 |

Question:
According to the table, what was the average score of the contestant from Texas in the competition?


id: b4f1cccbee7620602901988934f47abf
qtype: FactChecking
label: 9.266
Task: Table-QA (source dataset: TableBench)

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:
| province      |   population (2004 estimate) |   area (km square) |   density |   gdp (2003 , pps in mil ) |   gdp per cap (2003 , in ) |
|:--------------|-----------------------------:|-------------------:|----------:|---------------------------:|---------------------------:|
| south holland |                      3453000 |               2860 |    1207.3 |                      95868 |                      27825 |
| north holland |                      2583900 |               2660 |     971.4 |                      65295 |                      27169 |
| utrecht       |                      1159200 |               1356 |     854.9 |                      38355 |                      33148 |
| limburg       |                      1143000 |               2167 |     527.5 |                      28038 |                      24585 |
| north brabant |                      2406900 |               4938 |     487.4 |                      65295 |                      27169 |
| gelderland    |                      1967600 |               4995 |     393.9 |                      45043 |                      22942 |
| overijssel    |                      1105800 |               3337 |     331.4 |                      25854 |                      23441 |
| flevoland     |                       356400 |               1426 |     249.9 |                       6915 |                      19439 |
| groningen     |                       575900 |               2344 |     245.7 |                      18496 |                      32245 |
| zeeland       |                       378300 |               1792 |     211.1 |                       9354 |                      24706 |
| friesland     |                       642500 |               3361 |     191.2 |                      13989 |                      21830 |
| drenthe       |                       482300 |               2652 |     181.9 |                      10323 |                      21427 |

Question:
If the GDP per capita of flevoland decreases by 37%, what would be the new GDP per capita?


id: 020c4e86f2a942c2b0dbebb4919584d2
qtype: NumericalReasoning
label: 12246.57
Task: Table-QA (source dataset: TableBench)

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:
|   year | design          | issue                   | artist        |   mintage |   issue price |
|-------:|:----------------|:------------------------|:--------------|----------:|--------------:|
|   2003 | niagara falls   | hologram                | gary corcoran |     29967 |         79.95 |
|   2003 | rocky mountains | colorized               | josé osio     |     28793 |         69.95 |
|   2004 | iceberg         | hologram                | josé osio     |     24879 |         69.95 |
|   2004 | northern lights | double image hologram   | gary corcoran |     34135 |         79.95 |
|   2004 | hopewell rocks  | selectively gold plated | josé osio     |     16918 |         69.95 |
|   2005 | diamonds        | double image hologram   | josé osio     |     35000 |         69.95 |

Question:
What is the total mintage of coins issued in 2004?


id: 3c12603df3f93729c1be1358706a887f
qtype: NumericalReasoning
label: 75932
Task: Table-QA (source dataset: TableBench)

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:
| year        |   district - wide |   high schools |   middle schools |   elementary schools |   other programs & adjustments |
|:------------|------------------:|---------------:|-----------------:|---------------------:|-------------------------------:|
| 2006 - 2007 |             31221 |           8808 |             6405 |                14369 |                           1639 |
| 2005 - 2006 |             31599 |           8570 |             6610 |                14249 |                           2170 |
| 2004 - 2005 |             31851 |           8620 |             6876 |                14384 |                           1971 |
| 2003 - 2004 |             32150 |           8430 |             7115 |                14497 |                           2108 |
| 2002 - 2003 |             32464 |           8696 |             7103 |                14733 |                           1932 |
| 2001 - 2002 |             35399 |          10114 |             5504 |                19541 |                            240 |

Question:
What is the average annual change in the 'district-wide' budget from 2001-2002 to 2006-2007?


id: a9196b8ddb587ea972419f2fec183f52
qtype: NumericalReasoning
label: 835.6
Task: Table-QA (source dataset: TableBench)

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:
| peak            | country                                   |   elevation (m) |   prominence (m) |   col (m) |
|:----------------|:------------------------------------------|----------------:|-----------------:|----------:|
| mount stanley   | democratic republic of the congo / uganda |            5109 |             3951 |      1158 |
| mount karisimbi | rwanda / democratic republic of the congo |            4507 |             3312 |      1195 |
| kinyeti         | south sudan                               |            3187 |             2120 |      1067 |
| emogadong       | south sudan                               |            2623 |             1730 |       893 |
| kabobo          | democratic republic of the congo          |            2725 |             1604 |      1121 |
| mont mohi       | democratic republic of the congo          |            3480 |             1592 |      1888 |
| wuhevi          | democratic republic of the congo          |            3095 |             1570 |      1525 |
| mount muhabura  | rwanda / uganda                           |            4127 |             1530 |      2597 |

Question:
What is the average prominence of mountain peaks in the Democratic Republic of the Congo that have an elevation of at least 3000 meters?


id: c8a0829ce6f11dd2af255ba6d1e54552
qtype: NumericalReasoning
label: 2606.25
Task: Table-QA (source dataset: TableBench)

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:
| Model             |      8A |     8Aa |     8Ab | 8B      | 8F   |
|:------------------|--------:|--------:|--------:|:--------|:-----|
| Bore (mm)         |  120    |  120    |  120    | 120     | 140  |
| Stroke (mm)       |  130    |  130    |  130    | 130     | 150  |
| Displacement (l)  |   11.76 |   11.76 |   11.76 | 18.47   | -    |
| Compression ratio |    4.7  |    4.7  |    5.3  | 5.3     | 5.3  |
| Length (m)        |    1.19 |    1.25 |    1.31 | 1.36    | 1.32 |
| Width (m)         |    0.81 |    0.83 |    0.85 | 0.86    | 0.89 |
| Height (m)        |    0.77 |    0.81 |    0.87 | 0.90    | 0.88 |
| Weight(kg)        |  195    |  215    |  230    | 236     | 256  |
| Power output (hp) |  140    |  150    |  180    | 200/235 | 300  |
| at (rpm)          | 1900    | 2000    | 2100    | 2300    | 2100 |

Question:
Can you rank the models from highest to lowest power output (hp)?


id: 4af852836dd997ea05b065d0c530910b
qtype: NumericalReasoning
label: Model 8F，Model 8B，Model 8Ab，Model 8Aa，Model 8A
Task: Table-QA (source dataset: TableBench)

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:
| Particulars         | Total   | Male    | Female   |
|:--------------------|:--------|:--------|:---------|
| Total No. of Houses | 122     | -       | -        |
| Population          | 524     | 261     | 263      |
| Child (0-6)         | 95      | 46      | 49       |
| Schedule Caste      | 275     | 137     | 138      |
| Schedule Tribe      | 0       | 0       | 0        |
| Literacy            | 60.14 % | 65.12 % | 55.14 %  |
| Total Workers       | 194     | 143     | 51       |
| Main Worker         | 194     | 0       | 0        |
| Marginal Worker     | 0       | 0       | 0        |

Question:
Which demographic category has the highest percentage value among Male and Female in the given table?


id: 910bce6a7c6d7346fb3efa20a9469d9f
qtype: NumericalReasoning
label: Literacy
Task: Table-QA (source dataset: TableBench)

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:
|   year |   indians admitted |   pakistanis admitted |   sri lankans admitted |   bangladeshis admitted |   nepalis admitted |
|-------:|-------------------:|----------------------:|-----------------------:|------------------------:|-------------------:|
|   2000 |              26122 |                 14201 |                   5849 |                    2715 |                247 |
|   2001 |              27901 |                 15353 |                   5520 |                    3393 |                273 |
|   2002 |              28838 |                 14173 |                   4968 |                    2615 |                418 |
|   2003 |              24595 |                 12351 |                   4448 |                    1896 |                440 |
|   2004 |              25573 |                 12793 |                   4134 |                    3374 |                594 |
|   2005 |              22141 |                 13575 |                   4690 |                    3940 |                714 |
|   2006 |              30746 |                 12329 |                   4490 |                    3838 |                640 |
|   2007 |              26047 |                  9545 |                   3934 |                    2735 |                564 |
|   2008 |              24548 |                  8051 |                   4508 |                    2716 |                639 |
|   2009 |              26117 |                  6213 |                   4270 |                    4270 |                627 |
|   2010 |              30252 |                  4986 |                   4181 |                    4364 |               1502 |
|   2011 |              24965 |                  6073 |                   3104 |                    2449 |               1249 |
|   2012 |              28943 |                  9931 |                   3152 |                    2449 |               1311 |

Question:
How many years had more than 25000 Indians admitted?


id: 07f3911a00b6469405023dc34740b916
qtype: NumericalReasoning
label: 9
Task: Table-QA (source dataset: TableBench)

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:
|   year |   bötzow |   schwante |   vehlefanz |   neu - vehlefanz |   marwitz |   bärenklau |   eichstädt |
|-------:|---------:|-----------:|------------:|------------------:|----------:|------------:|------------:|
|   2004 |    2.785 |      1.983 |       1.771 |               340 |     1.407 |       1.291 |         942 |
|   2005 |    2.904 |      1.997 |       1.777 |               348 |     1.4   |       1.294 |         939 |
|   2006 |    2.973 |      2.061 |       1.814 |               391 |     1.432 |       1.33  |         926 |
|   2007 |    2.947 |      2.061 |       1.821 |               379 |     1.435 |       1.313 |         929 |
|   2008 |    2.937 |      2.043 |       1.8   |               355 |     1.398 |       1.294 |         876 |
|   2009 |    2.967 |      2.039 |       1.759 |               365 |     1.417 |       1.27  |         848 |
|   2010 |    2.981 |      2.089 |       1.765 |               385 |     1.429 |       1.288 |         850 |

Question:
In which year did the value in `bötzow` increase the most compared to the previous year?


id: 8dcdb337eb9607dcb80c77dae5ac6e20
qtype: NumericalReasoning
label: 2005
Task: Table-QA (source dataset: TableBench)

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:
|   rank by average |   place | couple           |   total points |   number of dances |   average |
|------------------:|--------:|:-----------------|---------------:|-------------------:|----------:|
|                 1 |       1 | brooke & derek   |            433 |                 16 |      27.1 |
|                 2 |       2 | warren & kym     |            397 |                 16 |      24.8 |
|                 3 |       3 | lance & lacey    |            392 |                 16 |      24.5 |
|                 4 |       5 | maurice & cheryl |            252 |                 11 |      22.9 |
|                 5 |       4 | cody & julianne  |            292 |                 13 |      22.5 |
|                 6 |       8 | toni b & alec    |            134 |                  6 |      22.3 |
|                 7 |       6 | susan & tony d   |            192 |                  9 |      21.3 |
|                 8 |      10 | misty & maksim   |             63 |                  3 |      21   |
|                 9 |      12 | ted & inna       |             37 |                  2 |      18.5 |
|                10 |      11 | kim k & mark     |             54 |                  3 |      18   |
|                11 |       9 | rocco & karina   |             89 |                  5 |      17.8 |
|                12 |       7 | cloris & corky   |            121 |                  7 |      17.3 |

Question:
How much higher is the average score of the top-ranked couple compared to the average score of the bottom-ranked couple?


id: 0e1c11b51f0f810b21d0e25a20b82fc1
qtype: NumericalReasoning
label: 9.8
Task: Table-QA (source dataset: TableBench)

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:
|   season |   overall | slalom   |   giant slalom |   super g | downhill   | combined   |
|---------:|----------:|:---------|---------------:|----------:|:-----------|:-----------|
|     1990 |        44 | -        |             39 |        12 | -          | 21         |
|     1991 |        15 | -        |             29 |         3 | 13         | 12         |
|     1992 |         3 | -        |             10 |         4 | 1          | -          |
|     1993 |         2 | 58       |              7 |         1 | 1          | 7          |
|     1994 |         3 | 49       |              6 |         1 | 1          | 19         |
|     1995 |         2 | 19       |              9 |         1 | 3          | 4          |
|     1996 |         1 | 39       |              2 |         1 | 2          | -          |
|     1997 |         2 | 19       |              2 |         2 | 5          | -          |
|     1998 |         1 | 12       |              6 |         1 | 1          | 2          |

Question:
In which season did the skier achieve a giant slalom ranking of 7?


id: 8b3679190263b8ff21f47df999a55756
qtype: FactChecking
label: 1993
Task: Table-QA (source dataset: TableBench)

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:
| Player       |   Games Played |   Field Goals |   Free Throws |   Points |
|:-------------|---------------:|--------------:|--------------:|---------:|
| Ralf Woods   |             16 |            54 |            70 |      178 |
| Clyde Alwood |             15 |            57 |             0 |      114 |
| Ernest McKay |             15 |            39 |             3 |       81 |
| Ray Woods    |             16 |            19 |             0 |       38 |
| John Felmley |              6 |             7 |             4 |       18 |
| George Halas |             11 |             5 |             0 |       10 |
| R.C. Haas    |              3 |             1 |             0 |        2 |
| Gordon Otto  |              4 |             1 |             0 |        2 |

Question:
How many total field goals were scored by all players who played 15 games or more?


id: 9ab870fb9dbf99e35b45ed0809178a22
qtype: NumericalReasoning
label: 169
Task: Table-QA (source dataset: TableBench)

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:
| Player            |   Rec. | Yards   | Avg.   |   TD's | Long   |
|:------------------|-------:|:--------|:-------|-------:|:-------|
| Charles Frederick |    115 | 1385    | 12     |     27 | 42     |
| Jerel Myers       |    104 | 1183    | 11.4   |     21 | 38     |
| Anthony Hines     |     58 | 822     | 14.2   |     12 | 39     |
| Boo Williams      |     45 | 474     | 10.5   |     17 | 35     |
| Ira Gooch         |     24 | 339     | 14.1   |      6 | 32     |
| Sam Simmons       |     15 | 197     | 13.1   |      2 | 30     |
| Kevin Beard       |     10 | 87      | 8.7    |      0 | 21     |
| Dawan Moss        |      7 | 39      | 5.6    |      1 | 12     |
| Cyron Brown       |      3 | 17      | 5.7    |      1 | 8      |
| Larrell Johnson   |      3 | 14      | 4.7    |      0 | 6      |
| Jamarr Wood       |      1 | 13      | 13     |      0 | 13     |
| Cecil Moore       |      2 | 9       | 4.5    |      2 | 8      |
| Raymond Philyaw   |      1 | −6      | −6     |      0 | −6     |

Question:
Which player had an average of 11.4 yards per reception?


id: 78ccc4fb07ce60975392c8b42aa454ea
qtype: FactChecking
label: Jerel Myers
Task: Table-QA (source dataset: TableBench)

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:
|   rank | team name                                         |   basic elements |   tumbling |   stunts |   tosses / pyramids | deductions   |   total |
|-------:|:--------------------------------------------------|-----------------:|-----------:|---------:|--------------------:|:-------------|--------:|
|      1 | school of saint anthony ssa seagulls              |             61.5 |       66.5 |     67.5 |                69.5 | (13)         |   252   |
|      2 | school of the holy spirit shs pep squad           |             64.5 |       63   |     66   |                64.5 | (15)         |   243   |
|      5 | pcc pep squad                                     |             55   |       49   |     65   |                64   | (26)         |   207   |
|      6 | assumption college ac hardcourt                   |             59   |       53   |     62   |                48.5 | (37)         |   185.5 |
|      8 | the cmic fighting vanguards                       |             47   |       36.5 |     57.5 |                56.5 | (35)         |   162.5 |
|      9 | de la salle zobel dlsz pep squad and cheerdancers |             46.5 |       44.5 |     54   |                44   | (27)         |   162   |

Question:
What is the average score in the 'tumbling' category across all teams?


id: accf35669852e1aaaf42099aaeb188bb
qtype: NumericalReasoning
label: 52.08
Task: Table-QA (source dataset: TableBench)

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:
|   rank | peak                     | country     | island       |   elevation (m) |   prominence (m) |   col (m) |
|-------:|:-------------------------|:------------|:-------------|----------------:|-----------------:|----------:|
|      1 | aoraki / mount cook      | new zealand | south island |            3755 |             3755 |         0 |
|      2 | mount ruapehu            | new zealand | north island |            2797 |             2797 |         0 |
|      3 | mount aspiring / tititea | new zealand | south island |            3033 |             2471 |       562 |
|      4 | mount taranaki / egmont  | new zealand | north island |            2518 |             2308 |       210 |
|      5 | mount tutoko             | new zealand | south island |            2723 |             2191 |       532 |
|      6 | mount tapuaenuku         | new zealand | south island |            2884 |             2021 |       863 |
|      7 | single cone              | new zealand | south island |            2319 |             1969 |       350 |
|      8 | manakau                  | new zealand | south island |            2608 |             1798 |       810 |
|      9 | mount taylor             | new zealand | south island |            2333 |             1636 |       698 |

Question:
Can you rank the top 3 mountains in New Zealand by their elevation in meters from highest to lowest?


id: 2a01a6240ddabb477a15919fcca82afb
qtype: NumericalReasoning
label: Aoraki / Mount Cook， Mount Aspiring / Tititea ， Mount Tapuaenuku
Task: Table-QA (source dataset: TableBench)

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:
| rank   | city                |   population |   area (km 2 ) |   density (inhabitants / km 2 ) |   altitude (mslm) |
|:-------|:--------------------|-------------:|---------------:|--------------------------------:|------------------:|
| 1st    | alessandria         |        94191 |         203.97 |                           461.8 |                95 |
| 2nd    | casale monferrato   |        36039 |          86.32 |                           417.5 |               116 |
| 3rd    | novi ligure         |        28581 |          54.22 |                           527.1 |               197 |
| 4th    | tortona             |        27476 |          99.29 |                           276.7 |               122 |
| 5th    | acqui terme         |        20426 |          33.42 |                           611.2 |               156 |
| 6th    | valenza             |        20282 |          50.05 |                           405.2 |               125 |
| 7th    | ovada               |        11912 |          35.33 |                           337.2 |               186 |
| 8th    | serravalle scrivia  |         6445 |          16.02 |                           402.3 |               225 |
| 9th    | arquata scrivia     |         6260 |          30.36 |                           206.2 |               248 |
| 10th   | castelnuovo scrivia |         5473 |          45.42 |                           120.5 |                85 |

Question:
What is the difference in population between the 6th ranked city and the city 'acqui terme'?


id: aec52e6703eb3d70fd4ff9a2e54cbd0b
qtype: NumericalReasoning
label: 144