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 | theme                     | artist                |   mintage |   issue price |
|-------:|:--------------------------|:----------------------|----------:|--------------:|
|   2002 | 15th anniversary loonie   | dora de pãdery - hunt |     67672 |         39.95 |
|   2004 | jack miner bird sanctuary | susan taylor          |     46493 |         39.95 |
|   2005 | tufted puffin             | n / a                 |     39818 |         39.95 |
|   2006 | snowy owl                 | glen loates           |     39935 |         44.95 |
|   2007 | trumpeter swan            | kerri burnett         |     40000 |         45.95 |
|   2008 | common eider              | mark hobson           |     40000 |         47.95 |
|   2009 | great blue heron          | chris jordison        |     40000 |         47.95 |
|   2010 | northern harrier          | arnold nogy           |     35000 |         49.95 |
|   2011 | great gray owl            | arnold nogy           |     35000 |         49.95 |
|   2012 | 25th anniversary loonie   | arnold nogy           |     35000 |         49.95 |

Question:
What is the total mintage of coins issued in the first 5 years (2002-2006) of the provided data?


id: afa6ff00100fcbf8556766a96d5e12f7
qtype: NumericalReasoning
label: 193918
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:
| class   | wheel arrangement   | railway   |   number at doncaster |   number at pyewipe |   number at march |
|:--------|:--------------------|:----------|----------------------:|--------------------:|------------------:|
| d13     | 4 - 4 - 0           | ger       |                     3 |                   3 |                 6 |
| d14     | 4 - 4 - 0           | ger       |                     0 |                   0 |                 1 |
| d15     | 4 - 4 - 0           | ger       |                     1 |                   0 |                 4 |
| e4      | 2 - 4 - 0           | ger       |                     1 |                   0 |                 4 |
| j14     | 0 - 6 - 0           | ger       |                     0 |                   0 |                 1 |
| j15     | 0 - 6 - 0           | ger       |                     0 |                   3 |                17 |
| j16     | 0 - 6 - 0           | ger       |                     0 |                   1 |                 7 |
| j17     | 0 - 6 - 0           | ger       |                     0 |                   2 |                15 |
| j18     | 0 - 6 - 0           | ger       |                     0 |                   0 |                 7 |
| j19     | 0 - 6 - 0           | ger       |                     0 |                   0 |                 8 |
| j20     | 0 - 6 - 0           | ger       |                     0 |                   0 |                14 |
| j66     | 0 - 6 - 0t          | ger       |                     0 |                   3 |                10 |
| j67     | 0 - 6 - 0t          | ger       |                     0 |                   0 |                 1 |
| j68     | 0 - 6 - 0t          | ger       |                     0 |                   0 |                 1 |

Question:
What is the total number of locomotives at Doncaster and Pyewipe combined for the 'j17' and 'e4' classes?


id: 5fff0c0fb4be0e28ec40c3b1dcbcd84b
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:
| Country                 | Primary   | Middle   | Diploma   | Career-related   | Schools   |
|:------------------------|:----------|:---------|:----------|:-----------------|:----------|
| United States           | 500       | 618      | 893       | 77               | 1,725     |
| Canada                  | 82        | 169      | 171       | 2                | 366       |
| Australia               | 119       | 45       | 67        | 1                | 176       |
| Ecuador                 | 9         | 9        | 253       | 0                | 253       |
| United Kingdom          | 14        | 13       | 125       | 13               | 132       |
| India                   | 63        | 21       | 108       | 0                | 128       |
| Mexico                  | 55        | 35       | 66        | 1                | 106       |
| China                   | 37        | 27       | 83        | 1                | 101       |
| Spain                   | 11        | 14       | 93        | 0                | 95        |
| Germany                 | 23        | 11       | 67        | 2                | 71        |
| Hong Kong               | 32        | 9        | 29        | 1                | 56        |
| Turkey                  | 25        | 10       | 43        | 0                | 60        |
| Argentina               | 7         | 3        | 56        | 0                | 57        |
| Switzerland             | 18        | 11       | 42        | 1                | 49        |
| Indonesia               | 32        | 14       | 29        | 0                | 48        |
| Poland                  | 6         | 8        | 40        | 0                | 45        |
| -                       | Primary   | Middle   | Diploma   | Career-related   | Schools   |
| Total Schools Globally  | 1,375     | 1,264    | 2,997     | 118              | 4,460     |
| Countries & Territories | 104       | 97       | 140       | 18               | 151       |

Question:
What is the difference between the total number of Primary schools in the top 3 countries with the most Primary schools and the total number of Career-related schools in all countries?


id: 5111df4c8ab0075f11805502915ebcf7
qtype: NumericalReasoning
label: 583
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:
| jurisdiction             |   for prohibition |   percent for |   against prohibition |   percent against |
|:-------------------------|------------------:|--------------:|----------------------:|------------------:|
| alberta and saskatchewan |              6238 |          68.8 |                  2824 |              31.2 |
| british columbia         |              5731 |          54.6 |                  4756 |              45.4 |
| manitoba                 |             12419 |          80.6 |                  2978 |              19.4 |
| new brunswick            |             26919 |          72.2 |                  9575 |              27.7 |
| nova scotia              |             34368 |          87.2 |                  5370 |              12.8 |
| ontario                  |            154498 |          57.3 |                115284 |              42.7 |
| prince edward island     |              9461 |          89.2 |                  1146 |              10.8 |
| quebec                   |             28436 |          18.8 |                122760 |              81.2 |

Question:
How many jurisdictions had more than 70% of votes in favor of prohibition?


id: d0a81a29b19bb9b01e0e01329ad80112
qtype: NumericalReasoning
label: 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 terms of gold medals won?


id: 3fe39c5bce73bdbc9e6340b961bbefe7
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:
| city / municipality   |   no of barangays |   area (km square) |   population (2010 census) |   pop density (per km square) |
|:----------------------|------------------:|-------------------:|---------------------------:|------------------------------:|
| angono                |                10 |              26.22 |                     102407 |                       3905.68 |
| antipolo              |                16 |             306.1  |                     677741 |                       2214.12 |
| baras                 |                10 |              84.93 |                      32609 |                        383.95 |
| binangonan            |                40 |              66.34 |                     249872 |                       3766.54 |
| cainta                |                 7 |              42.99 |                     311845 |                       7253.9  |
| cardona               |                18 |              28.56 |                      47414 |                       1660.15 |
| jalajala              |                11 |              44.12 |                      30074 |                        681.64 |
| morong                |                 8 |              37.58 |                      52194 |                       1388.88 |
| pililla               |                 9 |              69.95 |                      59527 |                        850.99 |
| rodriguez             |                11 |             312.7  |                     280904 |                        898.32 |
| san mateo             |                15 |              55.09 |                     205255 |                       3725.81 |
| tanay                 |                19 |             200    |                      98879 |                        494.3  |
| taytay                |                 5 |              38.8  |                     288956 |                       7447.32 |

Question:
How many cities/municipalities have a population density of over 3000 per km square?


id: e98478f17f738dd3bdd2ff3352d71381
qtype: NumericalReasoning
label: 5
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:
| Age Group   | Both Gender   |      % | Male   |    %.1 | Female   |    %.2 |
|:------------|:--------------|-------:|:-------|-------:|:---------|-------:|
| All Ages    | 32,512        | 100    | 16,390 |  50.41 | 16, 122  |  49.59 |
| Under 1     | 1,053         |   3.24 | 531    |   3.24 | 522      |   3.24 |
| 1 - 2       | 1,281         |   3.94 | 654    |   3.99 | 627      |   3.89 |
| 3 - 4       | 1,889         |   5.81 | 970    |   5.92 | 919      |   5.7  |
| 5 - 6       | 1,892         |   5.82 | 990    |   6.04 | 902      |   5.6  |
| 7 - 9       | 2,877         |   8.85 | 1,480  |   9.03 | 1,397    |   8.67 |
| 10 - 14     | 4,428         |  13.62 | 2,293  |  13.99 | 2,135    |  13.24 |
| 15 - 17     | 2,396         |   7.37 | 1,260  |   7.69 | 1,136    |   7.04 |
| 18 - 21     | 2,656         |   8.17 | 1,287  |   7.85 | 1,370    |   8.5  |
| 22 - 35     | 5,673         |  17.45 | 2,840  |  17.33 | 2,833    |  17.57 |
| 36 - 45     | 3,352         |  10.31 | 1,660  |  10.13 | 1,692    |  10.49 |
| 46 - 59     | 2,923         |   8.99 | 1,442  |   8.8  | 1,481    |   9.18 |
| 60 & above  | 2,091         |   6.43 | 982    |   5.99 | 1,109    |   6.88 |
| TOTAL       | 32,512        | 100    | 16,390 | 100    | 16,122   | 100    |

Question:
What is the total number of individuals in the age groups between 10 and 35?


id: b24100d2cb5ed9ab25a7fdadf8258089
qtype: NumericalReasoning
label: 15,153
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:
| type         |   beam height (mm) |   flange width (mm) |   web thickness (mm) |   flange thickness (mm) |   weight (kg / m) |   cross - section area (cm 2 ) |   moment of inertia in torsion (j) (cm 4 ) |
|:-------------|-------------------:|--------------------:|---------------------:|------------------------:|------------------:|-------------------------------:|-------------------------------------------:|
| ismb 80      |                 80 |                  46 |                  3.8 |                     5.2 |               6   |                           7.64 |                                       0.7  |
| ismb 100     |                100 |                  55 |                  4.1 |                     5.7 |               8.1 |                          10.3  |                                       1.1  |
| ismb 120     |                120 |                  70 |                  4.4 |                     6.3 |              10.4 |                          13.2  |                                       1.71 |
| ismb 140     |                140 |                  73 |                  4.7 |                     6.9 |              12.9 |                          16.4  |                                       2.54 |
| ismb 750 137 |                753 |                 263 |                 11.5 |                    17   |             137   |                         175    |                                     137.1  |
| ismb 750 147 |                753 |                 265 |                 13.2 |                    17   |             147   |                         188    |                                     161.5  |
| ismb 750 173 |                762 |                 267 |                 14.4 |                    21.6 |             173   |                         221    |                                     273.6  |

Question:
Which beam type has the highest moment of inertia in torsion (j) among all the options?


id: 87d27673443cdd977986ee4fe7ece98b
qtype: NumericalReasoning
label: ismb 750 173
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:
| -                                        |   Total |   Male |   Female |
|:-----------------------------------------|--------:|-------:|---------:|
| Population                               |    7159 |   3645 |     3514 |
| Children aged below 6 years              |     913 |    479 |      434 |
| Scheduled caste                          |    1782 |    890 |      892 |
| Scheduled tribe                          |     744 |    383 |      361 |
| Literates                                |    4323 |   2642 |     1681 |
| Workers (all)                            |    3612 |   2007 |     1605 |
| Main workers (total)                     |    2187 |   1463 |      724 |
| Main workers: Cultivators                |     756 |    500 |      256 |
| Main workers: Agricultural labourers     |     830 |    443 |      387 |
| Main workers: Household industry workers |     107 |     86 |       21 |
| Main workers: Other                      |     494 |    434 |       60 |
| Non-workers (total)                      |    3547 |   1638 |     1909 |

Question:
Which gender has a higher number of literates, Male or Female?


id: ee32b677b3e51d25608fcdbef787f33b
qtype: NumericalReasoning
label: Male
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 | name                | city   | region         |   height (m) |   height (ft) |   floors |   estimated completion |
|-------:|:--------------------|:-------|:---------------|-------------:|--------------:|---------:|-----------------------:|
|      1 | leadenhall building | london | greater london |          225 |           737 |       48 |                   2014 |
|      2 | 52 - 54 lime street | london | greater london |          190 |           623 |       38 |                   2017 |
|      3 | 100 bishopsgate     | london | greater london |          172 |           564 |       40 |                   2015 |
|      4 | 1 blackfriars       | london | greater london |          163 |           535 |       52 |                   2018 |
|      5 | 20 fenchurch street | london | greater london |          160 |           525 |       36 |                   2014 |
|      6 | baltimore tower     | london | greater london |          150 |           495 |       45 |                   2016 |
|      7 | providence tower    | london | greater london |          136 |           446 |       44 |                   2015 |
|      8 | one the elephant    | london | greater london |          133 |           436 |       37 |                   2016 |
|      9 | 25 churchill place  | london | greater london |          130 |           427 |       23 |                   2014 |
|     10 | lots road tower 1   | london | greater london |          122 |           400 |       37 |                   2015 |
|     11 | lexicon tower       | london | greater london |          115 |           377 |       35 |                   2016 |

Question:
What is the average height (in meters) of the top 5 tallest buildings in the table?


id: b6ce5ae3244350599a7403a76a1f1c69
qtype: NumericalReasoning
label: 182
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   |
|-------:|:---------------------------------------------|:---------------------|:-----------|:--------------|:--------|
|   1992 | CARIFTA Games (U20)                          | Nassau, Bahamas      | 1st        | Discus throw  | 37.86 m |
|   1992 | CARIFTA Games (U20)                          | Nassau, Bahamas      | 3rd        | Javelin throw | 36.37 m |
|   1999 | Central American and Caribbean Championships | Bridgetown, Barbados | 2nd        | Javelin throw | 54.24 m |
|   2000 | Olympic Games                                | Sydney, Australia    | 21st (q)   | Javelin throw | 56.36 m |
|   2005 | Central American and Caribbean Championships | Nassau, Bahamas      | 2nd        | Javelin throw | 61.10 m |
|   2005 | World Championships                          | Helsinki, Finland    | 14th (q)   | Javelin throw | 58.49 m |
|   2006 | Commonwealth Games                           | Melbourne, Australia | 3rd        | Javelin throw | 58.27 m |
|   2006 | Central American and Caribbean Games         | Cartagena, Colombia  | 4th        | Javelin throw | 56.82 m |
|   2008 | Olympic Games                                | Beijing, China       | 34th (q)   | Javelin throw | 55.51 m |
|   2011 | Pan American Games                           | Guadalajara, Mexico  | 7th        | Javelin throw | 51.40 m |

Question:
In which year did the athlete achieve their highest ranking in the Javelin throw event at the Olympic Games?


id: 7b6040473988da74ffaf42edf90be4a9
qtype: FactChecking
label: 2000
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                        | composition                 |   mintage |   issue price |
|-------:|:--------------------------|:------------------------------|:----------------------------|----------:|--------------:|
|   2008 | newfoundland and labrador | royal canadian mint engravers | 58.33% gold , 41.67% silver |      1000 |       1541.95 |
|   2008 | alberta                   | royal canadian mint engravers | 58.33% gold , 41.67% silver |      1000 |       1631.95 |
|   2009 | yukon                     | royal canadian mint engravers | 58.33% gold , 41.67% silver |      1000 |       1659.95 |
|   2009 | prince edward island      | royal canadian mint engravers | 58.33% gold , 41.67% silver |      1000 |       1949.95 |
|   2010 | british columbia          | royal canadian mint engravers | 58.33% gold , 41.67% silver |       500 |       2249.95 |
|   2010 | new brunswick             | royal canadian mint engravers | 58.33% gold , 41.67% silver |       500 |       2249.95 |

Question:
How much did the average issue price increase the most compared to the previous year?


id: be503c55c3cf1fbec022f0311349e163
qtype: NumericalReasoning
label: 445
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 ( wjc ) |   rank (arda) | metro area    |   number of jews (wjc) |   number of jews (asarb) |
|---------------:|--------------:|:--------------|-----------------------:|-------------------------:|
|              1 |             1 | new york city |                1750000 |                  2028200 |
|              2 |             3 | miami         |                 535000 |                   337000 |
|              3 |             2 | los angeles   |                 490000 |                   662450 |
|              4 |             4 | philadelphia  |                 254000 |                   285950 |
|              5 |             6 | chicago       |                 248000 |                   265400 |
|              6 |             8 | san francisco |                 210000 |                   218700 |
|              7 |             7 | boston        |                 208000 |                   261100 |

Question:
If the total number of Jews in the top 3 metro areas is approximately 2,200,000, what is the average number of Jews in each of these metro areas?


id: 2c2b2f4c7e4731dc5f241888ad978878
qtype: NumericalReasoning
label: 733,333.33
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 |   number of examinees |   number of passed students | pass percentage   |   obtained gpa - 5 |
|-------:|----------------------:|----------------------------:|:------------------|-------------------:|
|   2005 |                   314 |                         239 | 67.75%            |                 31 |
|   2006 |                   331 |                         278 | 72.37%            |                 54 |
|   2007 |                   336 |                         260 | 68.62%            |                 63 |
|   2008 |                   346 |                         274 | 75.54%            |                 79 |
|   2009 |                   360 |                         297 | 78.35%            |                 83 |
|   2010 |                   364 |                         322 | 79.68%            |                 85 |

Question:
What is the percentage increase in the number of passed students from 2005 to 2010?


id: 73a54b17717bad013f15c02d5d9b870e
qtype: NumericalReasoning
label: 34.73%
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:
| locomotive     | type        | builder                         | builder 's no   |   built |   entered service |   withdrawn |
|:---------------|:------------|:--------------------------------|:----------------|--------:|------------------:|------------:|
| 2              | 0 - 6 - 0st | beyer peacock & co              | 2575            |    1884 |              1884 |        1938 |
| 3              | 0 - 6 - 0st | beyer peacock & co              | 4558            |    1903 |              1903 |        1920 |
| 62xx           | 0 - 6 - 0   | robert stephenson and company   | 2195            |    1874 |              1903 |        1927 |
| 2020           | 2 - 6 - 4t  | beyer peacock & co              | 3206            |    1891 |              1834 |        1955 |
| 2017           | 2 - 6 - 4t  | beyer peacock & co              | 3289            |    1891 |              1939 |        1956 |
| 1              | 2 - 6 - 2t  | robert stephenson and hawthorns | e7841           |    1955 |              1955 |        1967 |
| j & a brown 26 | 2 - 6 - 4t  | beyer peacock & co              | 2567            |    1885 |              1967 |        1967 |
| 3013           | 4 - 6 - 4t  | beyer peacock & co              | 4456            |    1903 |              1967 |        1976 |

Question:
Locomotive Service Life is defined as the duration between the 'entered service' and 'withdrawn' dates for a locomotive. Based on this definition, what was the longest Locomotive Service Life of the locomotive?


id: 13268aef491b17ad2d89c67d8bfa336d
qtype: NumericalReasoning
label: 121
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 |
| total  |             346788 |                139574 |                  57248 |                   35856 |               9218 |

Question:
What is the average number of Indians admitted per year from 2000 to 2010?


id: 9ed3912eda93df5274890d914b69329e
qtype: NumericalReasoning
label: 26625
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:
| chambering         |   p1 diameter (mm) |   a external (cm 2 ) |   p max ( bar ) |   f bolt ( kgf ) | f bolt    |
|:-------------------|-------------------:|---------------------:|----------------:|-----------------:|:----------|
| .22 long rifle     |               5.74 |               0.2587 |            1650 |              435 | n (lbf)   |
| 9x19 mm parabellum |               9.93 |               0.7744 |            2350 |             1820 | n ( lbf ) |
| .357 sig           |              10.77 |               0.911  |            3050 |             2779 | n (lbf)   |
| .380 acp           |               9.7  |               0.739  |            1500 |             1130 | n (lbf)   |
| .40 s&w            |              10.77 |               0.911  |            2250 |             2050 | n (lbf)   |
| 10 mm auto         |              10.81 |               0.9178 |            2300 |             2111 | n (lbf)   |
| .45 acp            |              12.09 |               1.1671 |            1300 |             1517 | n (lbf)   |
| .454 casull        |              12.13 |               1.1556 |            3900 |             4507 | n (lbf)   |

Question:
Which chambering has the highest maximum pressure (p max) in bars?


id: 8d2c0f071a634bd6233252d4a2f97d91
qtype: NumericalReasoning
label: .454 casull
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 | puncak jaya (carstensz pyramid) | indonesia | new guinea |            4884 |             4884 |         0 |
|      2 | mount arfak                     | indonesia | new guinea |            2940 |             2761 |       179 |
|      3 | puncak mandala                  | indonesia | new guinea |            4760 |             2760 |      2000 |
|      4 | mount kobowre                   | indonesia | new guinea |            3750 |             2217 |      1533 |
|      5 | mount gauttier                  | indonesia | new guinea |            2230 |             2007 |       223 |
|      6 | mount wondiwoi                  | indonesia | new guinea |            2180 |             1985 |       195 |
|      7 | bon irau                        | indonesia | new guinea |            2500 |             1900 |       600 |
|      8 | mount cycloop                   | indonesia | new guinea |            2000 |             1876 |       124 |
|      9 | undundi - wandandi              | indonesia | new guinea |            3640 |             1740 |      1900 |
|     10 | mount kumawa                    | indonesia | new guinea |            1680 |             1636 |        44 |
|     11 | angemuk                         | indonesia | new guinea |            3949 |             1565 |      2384 |

Question:
What is the total elevation of all mountains in the table?


id: 2438086f1b3d0cb3f63d46f4c9eb8dbf
qtype: NumericalReasoning
label: 34513
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 |   starts |   wins |   top 5 |   top 10 |   poles |   avg start |   avg finish |   winnings | position   | team (s)                                |
|-------:|---------:|-------:|--------:|---------:|--------:|------------:|-------------:|-----------:|:-----------|:----------------------------------------|
|   1983 |        5 |      0 |       0 |        0 |       0 |        25.6 |         30.4 |       8060 | 47th       | 5 sacks & sons                          |
|   1984 |       29 |      0 |       0 |        1 |       0 |        24.3 |         25.1 |      75183 | 19th       | 51 sacks & sons                         |
|   1986 |        8 |      0 |       0 |        1 |       0 |        22.4 |         30.4 |      64810 | 41st       | 10 digard motorsports                   |
|   1987 |       16 |      0 |       0 |        0 |       0 |        23.6 |         29.8 |      54815 | 33rd       | 50 dingman brothers racing              |
|   1990 |       16 |      0 |       2 |        4 |       1 |        18.6 |         20.8 |     216148 | 32nd       | 17 / 18 / 46 hendrick motorsports       |
|   1991 |       11 |      0 |       0 |        0 |       0 |        27.5 |         30.4 |      84215 | 39th       | 18 daytona speed inc 47 close racing    |
|   1992 |       20 |      0 |       0 |        0 |       0 |        23.5 |         25.1 |     178120 | 30th       | 41 larry hedrick motorsports            |
|   1993 |       19 |      0 |       0 |        1 |       0 |        24.3 |         24.2 |     168055 | 35th       | 9 melling racing 68 tristar motorsports |
|   1994 |       31 |      0 |       0 |        3 |       1 |        19.7 |         27   |     411728 | 31st       | 77 us motorsports inc                   |
|   1998 |        7 |      0 |       0 |        0 |       0 |        23.6 |         35.3 |     296880 | 53rd       | 98 yarborough - burdette motorsports    |
|   2004 |        3 |      0 |       0 |        0 |       0 |        36.3 |         41.7 |     154100 | 71st       | 13 daytona speed inc                    |

Question:
In which year did the driver earn $411,728 in winnings?


id: 3cebc683797d8ddec38b47f86d1c2eb0
qtype: FactChecking
label: 1994