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 | population   | Catholics (based on registration by the church itself)   |   Percentage (based on registration by the church itself) |
|-------:|:-------------|:---------------------------------------------------------|----------------------------------------------------------:|
|   1970 | 12,957,621   | 5,320,000                                                |                                                      40.5 |
|   1980 | 14,091,014   | 5,620,000                                                |                                                      39.5 |
|   1990 | 14,892,574   | 5,560,000                                                |                                                      37   |
|   1995 | 15,424,122   | 5,385,258                                                |                                                      34.8 |
|   2000 | 15,863,950   | 5,060,413                                                |                                                      31.6 |
|   2005 | 16,305,526   | 4,406,000                                                |                                                      27   |
|   2010 | 16,574,989   | 4,166,000                                                |                                                      25   |
|   2015 | 16,900,726   | 3,882,000                                                |                                                      22.9 |
|   2016 | 16,979,120   | 3,832,000                                                |                                                      22.4 |
|   2017 | 17,081,057   | 3,769,000                                                |                                                      21.9 |

Question:
In which year did the percentage of Catholics decrease the most compared to the previous year?


id: a9c67600eb25ab046e30bae4b5075d92
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:
| MGWR No.   | Name               | Builder       |   Introduced |   D-bogie |   GSR No. |   Withdrawn |
|:-----------|:-------------------|:--------------|-------------:|----------:|----------:|------------:|
| 2          | Jupiter            | Beyer-Peacock |         1880 |      1900 |       534 |        1949 |
| 3          | Juno               | Beyer-Peacock |         1880 |      1901 |       535 |        1949 |
| 25→4       | Cyclops            | Beyer-Peacock |         1880 |      1901 |       531 |        1945 |
| 26→5       | Britania           | Beyer-Peacock |         1880 |      1900 |       532 |        1949 |
| 36→1       | Empress of Austria | Beyer-Peacock |         1881 |      1900 |       530 |        1949 |
| 37→35→6    | Wolfdog            | Beyer-Peacock |         1881 |      1900 |       533 |        1953 |

Question:
How many more years was the 'Empress of Austria' in service compared to the 'Cyclops'?


id: 2617d273bcf353520cf20eae1c1f4259
qtype: NumericalReasoning
label: 3
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      | italy                 |      5 |        4 |        2 |      11 |
| 2      | france                |      3 |        3 |        5 |      11 |
| 3      | egypt                 |      2 |        0 |        2 |       4 |
| 4      | algeria               |      1 |        4 |        4 |       9 |
| 5      | tunisia               |      1 |        1 |        5 |       7 |
| 6      | turkey                |      1 |        1 |        0 |       2 |
| 7      | slovenia              |      1 |        0 |        1 |       2 |
| 8      | serbia and montenegro |      0 |        1 |        2 |       3 |
| 9      | spain                 |      0 |        0 |        5 |       5 |
| 10 =   | greece                |      0 |        0 |        1 |       1 |
| 10 =   | morocco               |      0 |        0 |        1 |       1 |

Question:
According to the table, which nation won 1 gold and 4 silver medals?


id: 0024501faeb895ca098242a0af2f822a
qtype: FactChecking
label: algeria
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 |   property taxes |   investment earnings |   other local sources |   state & federal |   total revenue |
|-------:|-----------------:|----------------------:|----------------------:|------------------:|----------------:|
|   2005 |      2.43849e+07 |      255041           |           2.67006e+06 |       1.3582e+07  |     4.08917e+07 |
|   2004 |      2.10992e+07 |      181103           |           2.62413e+06 |       1.39992e+07 |     3.79036e+07 |
|   2003 |      1.71992e+07 |      509862           |           2.30909e+06 |       1.27949e+07 |     3.25396e+07 |
|   2002 |      1.43592e+07 |      879398           |           2.1681e+06  |       1.51329e+07 |     3.25396e+07 |
|   2001 |      1.16312e+07 |           1.94988e+06 |           1.98744e+06 |       1.29295e+07 |     2.8498e+07  |
|   2000 |      1.06087e+07 |      493839           |           2.12748e+06 |       8.54956e+06 |     2.17796e+07 |

Question:
What is the average annual increase in 'property taxes' from 2000 to 2005?


id: 681a7859d2c55254bfe97804f56ba3ba
qtype: NumericalReasoning
label: 2755233.4
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 | germany        |     45 |       33 |       28 |     106 |
|      2 | switzerland    |     39 |       35 |       32 |     106 |
|      3 | italy          |     18 |       18 |        6 |      42 |
|      4 | united states  |     12 |       20 |       31 |      63 |
|      5 | west germany   |     11 |       13 |       12 |      36 |
|      6 | canada         |     11 |       11 |       12 |      34 |
|      7 | east germany   |      8 |        9 |        8 |      25 |
|      8 | great britain  |      7 |        6 |        4 |      17 |
|      9 | austria        |      6 |       11 |       14 |      31 |
|     10 | russia         |      2 |        5 |        4 |      11 |
|     11 | romania        |      2 |        2 |        2 |       6 |
|     12 | latvia         |      2 |        1 |        1 |       4 |
|     13 | belgium        |      1 |        1 |        1 |       3 |
|     14 | france         |      1 |        0 |        4 |       5 |
|     15 | new zealand    |      1 |        0 |        1 |       2 |
|     16 | czechoslovakia |      0 |        2 |        0 |       2 |
|     17 | sweden         |      0 |        0 |        2 |       2 |
|     17 | soviet union   |      0 |        0 |        2 |       2 |
|     19 | spain          |      0 |        0 |        1 |       1 |

Question:
Which nation ranked 4th in the medal count ?


id: 56af57cfe3097874ce49535911e9f039
qtype: FactChecking
label: united states
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:
What is the average magnitude of earthquakes that have resulted in a death toll of at least 1,000 and have a depth of less than 30 km?


id: dd778956ba0b5266e7a32a45bf8ab123
qtype: NumericalReasoning
label: 7.0
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:
|   # in office | Governor                | Days   |   Rank |
|--------------:|:------------------------|:-------|-------:|
|            11 | Calvin L. Rampton       | 4,382  |      1 |
|            14 | Mike Leavitt            | 3,957  |      2 |
|            17 | Gary Herbert            | 3,544  |      3 |
|             1 | Heber Manning Wells     | 3,283  |      4 |
|             7 | Henry H. Blood          | 2,926  |      5 |
|             9 | J. Bracken Lee          | 2,926  |      5 |
|            12 | Scott M. Matheson       | 2,926  |      5 |
|             3 | William Spry            | 2,919  |      8 |
|             6 | George Dern             | 2,919  |      8 |
|             8 | Herbert B. Maw          | 2,919  |      8 |
|            10 | George Dewey Clyde      | 2,919  |      8 |
|            13 | Norman H. Bangerter     | 2,919  |      8 |
|            16 | Jon Huntsman, Jr.       | 1,681  |     13 |
|             2 | John Christopher Cutler | 1,463  |     14 |
|             4 | Simon Bamberger         | 1,463  |     14 |
|             5 | Charles R. Mabey        | 1,463  |     14 |
|            15 | Olene S. Walker         | 425    |     17 |

Question:
Which governor served for a longer period, Calvin L. Rampton or Mike Leavitt?


id: 6f016ae8920e8b6c0534d39de0ddbdc9
qtype: NumericalReasoning
label: Calvin L. Rampton
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:
| state            |   1990 - 95 |   1996 - 00 |   2001 - 05 |   2006 - 10 |
|:-----------------|------------:|------------:|------------:|------------:|
| bihar            |        0.41 |        0.3  |        0.43 |        0.88 |
| gujarat          |        0.48 |        0.57 |        0.64 |        0.69 |
| andhra pradesh   |        0.53 |        0.73 |        0.55 |        0.61 |
| punjab           |        0.32 |        0.46 |        0.46 |        0.6  |
| jammu & kashmir  |        0.13 |        0.32 |        0.17 |        0.4  |
| haryana          |        0.33 |        0.6  |        0.31 |        0.37 |
| himachal pradesh |        0.26 |        0.14 |        0.23 |        0.35 |
| tamil nadu       |        0.19 |        0.2  |        0.24 |        0.29 |
| madhya pradesh   |        0.23 |        0.22 |        0.31 |        0.29 |
| karnataka        |        0.24 |        0.19 |        0.2  |        0.29 |
| rajasthan        |        0.27 |        0.23 |        0.26 |        0.27 |
| kerala           |        0.16 |        0.2  |        0.22 |        0.27 |
| maharashtra      |        0.45 |        0.29 |        0.27 |        0.26 |
| uttar pradesh    |        0.11 |        0.11 |        0.16 |        0.21 |
| orissa           |        0.22 |        0.16 |        0.15 |        0.19 |
| assam            |        0.21 |        0.02 |        0.14 |        0.17 |
| west bengal      |        0.11 |        0.08 |        0.03 |        0.01 |

Question:
How many states have a value greater than 0.3 in the 2001-05 time period?


id: 577472b9c44b101799d923f48cd30454
qtype: NumericalReasoning
label: 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:
| Year                | Competition                                                | Venue                      | Position            | Event               | Notes               |
|:--------------------|:-----------------------------------------------------------|:---------------------------|:--------------------|:--------------------|:--------------------|
| Representing Mexico | Representing Mexico                                        | Representing Mexico        | Representing Mexico | Representing Mexico | Representing Mexico |
| 1978                | Central American and Caribbean Junior Championships (U-17) | Xalapa, México             | 3rd                 | 1000 m              | 2:38.8 A            |
| 1978                | Central American and Caribbean Junior Championships (U-17) | Xalapa, México             | 1st                 | 3000 m              | 9:04.4 A            |
| 1980                | Central American and Caribbean Junior Championships (U-20) | Nassau, Bahamas            | 4th                 | 1500 m              | 3:53.7              |
| 1980                | Central American and Caribbean Junior Championships (U-20) | Nassau, Bahamas            | 2nd                 | 5000 m              | 14:27.4             |
| 1980                | Central American and Caribbean Junior Championships (U-20) | Nassau, Bahamas            | 1st                 | 3000 m steeplechase | 9:27.8              |
| 1984                | Olympic Games                                              | Los Angeles, United States | 36th                | Marathon            | 2:20:33             |
| 1988                | Ibero-American Championships                               | Ciudad de México, México   | 1st                 | 10,000m             | 29:51.09 A          |
| 1988                | Olympic Games                                              | Seoul, South Korea         | 11th                | Marathon            | 2:13:58             |

Question:
What is the competition where the athlete won 1st place in the 3000 m steeplechase event, which was held in a city that is also the capital of the Bahamas?


id: 691ee4d04b744fd879670b1a0075aaf7
qtype: FactChecking
label: Central American and Caribbean Junior Championships (U-20)
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:
|   election |   of candidates nominated |   of seats won |   of total votes | % of popular vote   |
|-----------:|--------------------------:|---------------:|-----------------:|:--------------------|
|       1945 |                       203 |             65 |          1448744 | 27.62%              |
|       1949 |                       249 |             41 |          1734261 | 29.62%              |
|       1953 |                       248 |             50 |          1749579 | 31.01%              |
|       1957 |                       256 |            109 |          2564732 | 38.81%              |
|       1958 |                       265 |            208 |          3908633 | 53.56%              |
|       1962 |                       265 |            114 |          2865542 | 37.22%              |
|       1963 |                       265 |             93 |          2582322 | 32.72%              |
|       1965 |                       265 |             95 |          2500113 | 32.41%              |
|       1968 |                       262 |             72 |          2548949 | 31.36%              |
|       1972 |                       265 |            107 |          3388980 | 35.02%              |
|       1974 |                       264 |             95 |          3371319 | 35.46%              |
|       1979 |                       282 |            136 |          4111606 | 35.89%              |
|       1980 |                       282 |            103 |          3552994 | 32.49%              |
|       1984 |                       282 |            211 |          6278818 | 50.03%              |
|       1988 |                       295 |            169 |          5667543 | 43.02%              |
|       1993 |                       295 |              2 |          2178303 | 16.04%              |
|       1997 |                       301 |             20 |          2446705 | 18.84%              |
|       2000 |                       291 |             12 |          1566994 | 12.19%              |

Question:
In which election year did the party achieve the highest percentage of popular vote?


id: f99e2389f5d1f9e1ea48c27d37ec0ec2
qtype: NumericalReasoning
label: 1958
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:
|   draw | artist           | song                         |   points |   place |
|-------:|:-----------------|:-----------------------------|---------:|--------:|
|      1 | niamh kavanagh   | in your eyes                 |      118 |       1 |
|      2 | suzanne bushnell | long gone                    |       54 |       7 |
|      3 | patricia roe     | if you changed your mind     |       75 |       3 |
|      4 | róisín ní haodha | mo mhúirnín óg               |       34 |       8 |
|      5 | champ            | 2nd time around              |       79 |       2 |
|      6 | off the record   | hold out                     |       61 |       6 |
|      7 | dav mcnamara     | stay                         |       67 |       4 |
|      8 | perfect timing   | why aren't we talking anyway |       62 |       5 |

Question:
How many more points did the artist with the highest points score compared to the artist with the second-highest points score?


id: 371bc736c7ec115f86c9e1a7ddd9c568
qtype: NumericalReasoning
label: 39
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 kilimanjaro | tanzania   |            5895 |             5885 |        10 |
| mount kenya       | kenya      |            5199 |             3825 |      1374 |
| mount meru        | tanzania   |            4565 |             3170 |      1395 |
| mount elgon       | uganda     |            4321 |             2458 |      1863 |
| mulanje massif    | malawi     |            3002 |             2319 |       683 |
| kimhandu          | tanzania   |            2653 |             2121 |       532 |
| mount satima      | kenya      |            4001 |             2081 |      1920 |
| mount hanang      | tanzania   |            3420 |             2050 |      1370 |
| loolmalassin      | tanzania   |            3682 |             2040 |      1642 |
| gelai peak        | tanzania   |            2948 |             1930 |      1018 |
| mount moroto      | uganda     |            3083 |             1818 |      1265 |
| kitumbeine hill   | tanzania   |            2858 |             1770 |      1088 |
| chepunyal hills   | kenya      |            3334 |             1759 |      1575 |
| mount namuli      | mozambique |            2419 |             1757 |       662 |
| shengena          | tanzania   |            2464 |             1750 |       714 |
| sungwi            | tanzania   |            2300 |             1730 |       570 |
| mount kadam       | uganda     |            3063 |             1690 |      1373 |
| mtorwi            | tanzania   |            2980 |             1688 |      1292 |
| mount kulal       | kenya      |            2285 |             1542 |       743 |
| karenga           | tanzania   |            2279 |             1529 |       750 |
| mount ng'iro      | kenya      |            2848 |             1501 |      1347 |

Question:
How many mountains in Tanzania have an elevation above 3000 meters and a prominence less than 3000?


id: 5a6a21f05be43637076dc55fd0420587
qtype: NumericalReasoning
label: 2
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:
|   sno | power plant     | state            |   commissioned capacity (mw) |   year of commission |
|------:|:----------------|:-----------------|-----------------------------:|---------------------:|
|     1 | baira siul      | himachal pradesh |                          180 |                 1981 |
|     2 | loktak          | manipur          |                          105 |                 1983 |
|     3 | salal - i       | jammu & kashmir  |                          345 |                 1987 |
|     4 | tanakpur        | uttarakhand      |                          120 |                 1992 |
|     5 | chamera - i     | himachal pradesh |                          540 |                 1994 |
|     6 | salal - ii      | jammu & kashmir  |                          345 |                 1996 |
|     7 | uri - i         | jammu & kashmir  |                          480 |                 1997 |
|     8 | rangit          | sikkim           |                           60 |                 1999 |
|     9 | chamera - ii    | himachal pradesh |                          300 |                 2004 |
|    10 | indira sagar    | madhya pradesh   |                         1000 |                 2005 |
|    11 | dhauliganga - i | uttarakhand      |                          280 |                 2005 |
|    12 | dul hasti       | jammu & kashmir  |                          390 |                 2007 |
|    13 | omkareshwar     | madhya pradesh   |                          520 |                 2007 |
|    14 | teesta - v      | sikkim           |                          510 |                 2008 |
|    15 | sewa - ii       | jammu & kashmir  |                          120 |                 2010 |
|    16 | chamera - iii   | himachal pradesh |                          231 |                 2012 |

Question:
What is the total commissioned capacity (in MW) of all power plants in Himachal Pradesh?


id: ac4ea376af826244678bb8ef6a0e024b
qtype: NumericalReasoning
label: 1251
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:
| hand                |   1 credit |   2 credits |   3 credits |   4 credits |   5 credits |
|:--------------------|-----------:|------------:|------------:|------------:|------------:|
| natural royal flush |        300 |         600 |         900 |        1200 |        4000 |
| four deuces         |        200 |         400 |         600 |         800 |        1000 |
| wild royal flush    |         25 |          50 |          75 |         100 |         125 |
| five of a kind      |         15 |          30 |          45 |          60 |          75 |
| straight flush      |          9 |          18 |          27 |          36 |          45 |
| four of a kind      |          5 |          10 |          15 |          20 |          25 |
| full house          |          3 |           6 |           9 |          12 |          15 |
| flush               |          2 |           4 |           6 |           8 |          10 |
| straight            |          2 |           4 |           6 |           8 |          10 |
| three of a kind     |          1 |           2 |           3 |           4 |           5 |

Question:
If a player wins with a "natural royal flush" and a "four of a kind" in two separate games, both with a 3-credit bet, how much would they win in total?


id: 94a9383e2a483fdd061810759e892812
qtype: NumericalReasoning
label: 915
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 | theme                    | artist          | finish                          |   issue price |   total mintage |
|-------:|:-------------------------|:----------------|:--------------------------------|--------------:|----------------:|
|   2002 | golden tulip             | anthony testa   | proof (selectively gold plated) |         24.95 |           19986 |
|   2003 | golden daffodil          | christie paquet | proof (selectively gold plated) |         34.95 |           36293 |
|   2004 | golden easter lily       | christie paquet | proof (selectively gold plated) |         34.95 |           23486 |
|   2005 | golden rose              | christie paquet | proof (selectively gold plated) |         34.95 |           23000 |
|   2006 | golden daisy             | christie paquet | proof (selectively gold plated) |         34.95 |           23000 |
|   2007 | golden forget - me - not | christie paquet | proof (selectively gold plated) |         38.95 |           20000 |

Question:
What is the average issue price of coins released between 2002 and 2005?


id: fbd83f8dbf53095ebbddef8abd5e4497
qtype: NumericalReasoning
label: 32.45
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:
| Color         |   Pin (Tip) |   Pin (Ring) | Color.1       |
|:--------------|------------:|-------------:|:--------------|
| White/Blue    |          26 |            1 | Blue/White    |
| White/Orange  |          27 |            2 | Orange/White  |
| White/Green   |          28 |            3 | Green/White   |
| White/Brown   |          29 |            4 | Brown/White   |
| White/Slate   |          30 |            5 | Slate/White   |
| Red/Blue      |          31 |            6 | Blue/Red      |
| Red/Orange    |          32 |            7 | Orange/Red    |
| Red/Green     |          33 |            8 | Green/Red     |
| Red/Brown     |          34 |            9 | Brown/Red     |
| Red/Slate     |          35 |           10 | Slate/Red     |
| Black/Blue    |          36 |           11 | Blue/Black    |
| Black/Orange  |          37 |           12 | Orange/Black  |
| Black/Green   |          38 |           13 | Green/Black   |
| Black/Brown   |          39 |           14 | Brown/Black   |
| Black/Slate   |          40 |           15 | Slate/Black   |
| Yellow/Blue   |          41 |           16 | Blue/Yellow   |
| Yellow/Orange |          42 |           17 | Orange/Yellow |
| Yellow/Green  |          43 |           18 | Green/Yellow  |
| Yellow/Brown  |          44 |           19 | Brown/Yellow  |
| Yellow/Slate  |          45 |           20 | Slate/Yellow  |
| Violet/Blue   |          46 |           21 | Blue/Violet   |
| Violet/Orange |          47 |           22 | Orange/Violet |
| Violet/Green  |          48 |           23 | Green/Violet  |
| Violet/Brown  |          49 |           24 | Brown/Violet  |
| Violet/Slate  |          50 |           25 | Slate/Violet  |

Question:
What is the average value of the "Pin (Tip)" column?


id: 1e0891ff9db2d97d00d2b1f5d12142cd
qtype: NumericalReasoning
label: 38
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:
|   rating |   share | rating / share (18 - 49)   |   viewers (millions) |   rank (overall) |
|---------:|--------:|:---------------------------|---------------------:|-----------------:|
|      5.4 |       9 | 2.6 / 7                    |                 9.2  |               27 |
|      4.4 |       7 | 2.6 / 6                    |                 7.81 |               34 |
|      6.6 |      11 | 3.0 / 8                    |                10.6  |               18 |
|      6.1 |      10 | 3.1 / 8                    |                10.13 |               28 |
|      5.9 |      10 | 3.1 / 8                    |                10.33 |               26 |
|      7.2 |      11 | 3.2 / 8                    |                12.42 |               15 |
|      7.1 |      11 | 3.8 / 10                   |                11.97 |               12 |
|      6.2 |      10 | 2.9 / 8                    |                10.58 |               18 |
|      6.1 |      10 | n / a                      |                10.31 |               20 |
|      6   |      10 | n / a                      |                10.27 |               17 |
|      6.8 |       9 | 2.0 / 7                    |                10.84 |               20 |
|      7.6 |      10 | n / a                      |                12.49 |               19 |

Question:
If the viewership of a particular show increases by 10% from 9.2 million, what would be the new viewership in millions?


id: 07ff0047fb0924e84ec62261007e0902
qtype: NumericalReasoning
label: 10.12
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   | route                                      |   avg daily flts |   of airlines |   distance (km) | market share leader   |
|:-------|:-------------------------------------------|-----------------:|--------------:|----------------:|:----------------------|
| 1      | seoul ( gmp ) - jeju ( cju )               |              159 |             7 |             451 | korean air            |
| 2      | rio de janeiro ( sdu ) - são paulo ( cgh ) |              125 |             4 |             359 | tam                   |
| 3      | mumbai ( bom ) - new delhi ( del )         |              123 |             8 |            1138 | jet airways           |
| 4      | tokyo ( hnd ) - sapporo ( cts )            |              119 |             4 |             822 | all nippon airways    |
| 5      | monte carlo ( mcm ) - nice ( nce )         |              117 |             2 |              18 | heli air monaco       |
| 6t     | madrid ( mad ) - barcelona ( bcn )         |              116 |             4 |             484 | iberia                |
| 6t     | melbourne ( mel ) - sydney ( syd )         |              116 |             8 |             705 | qantas                |
| 8      | kahului ( ogg ) - honolulu ( hnl )         |               98 |             4 |             163 | hawaiian airlines     |
| 9t     | johannesburg ( jnb ) - cape town ( cpt )   |               92 |             6 |            1270 | south african airways |
| 9t     | fukuoka ( fuk ) - tokyo ( hnd )            |               92 |             3 |             881 | japan airlines        |

Question:
If the average daily flights on the monte carlo ( mcm ) - nice ( nce ) route increase by 28%, how many average daily flights would there be on this route?


id: f4c1e5dc8a423e313f0c765c75cae345
qtype: NumericalReasoning
label: 149.76
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 |   episodes | timeslot (et)    | season premiere     | season finale    | tv season   |   rank |   viewers (in millions) |
|---------:|-----------:|:-----------------|:--------------------|:-----------------|:------------|-------:|------------------------:|
|        1 |         10 | saturday 8:00 pm | february 21 , 2004  | august 14 , 2004 | 2003 - 2004 |    123 |                    6.21 |
|        2 |         17 | saturday 8:00 pm | september 25 , 2004 | august 27 , 2005 | 2004 - 2005 |    107 |                    6.41 |
|        3 |         25 | saturday 8:00 pm | september 17 , 2005 | august 12 , 2006 | 2005 - 2006 |    126 |                    5.74 |
|        4 |         25 | saturday 8:00 pm | october 21 , 2006   | august 25 , 2007 | 2006 - 2007 |    180 |                    5.12 |
|        5 |         23 | saturday 8:00 pm | december 8 , 2007   | august 23 , 2008 | 2007 - 2008 |    160 |                    4.69 |
|        6 |         21 | saturday 8:00 pm | december 13 , 2008  | august 29 , 2009 | 2008 - 2009 |    149 |                    3.8  |
|        7 |         18 | saturday 8:00 pm | december 12 , 2009  | august 28 , 2010 | 2009 - 2010 |    119 |                    3.55 |
|        8 |         22 | saturday 8:00 pm | december 11 , 2010  | august 20 , 2011 | 2010 - 2011 |    170 |                    3.53 |
|        9 |         14 | saturday 8:00 pm | december 24 , 2011  | august 18 , 2012 | 2011 - 2012 |    156 |                    3.46 |

Question:
What is the average number of viewers (in millions) for the TV show during the seasons that had more than 20 episodes?


id: 2ac96562739ccc785f8b1db7407a7a33
qtype: NumericalReasoning
label: 4.576