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:
| agent             | melting / boiling point   |   effectiveness as blood agent |   persistence , open area |   persistence , enclosed area |   field stability |   storage stability |   toxicity as blood agent |
|:------------------|:--------------------------|-------------------------------:|--------------------------:|------------------------------:|------------------:|--------------------:|--------------------------:|
| hydrogen cyanide  | - 13 / 26 degree          |                             10 |                         2 |                             9 |                10 |                   8 |                        10 |
| cyanogen          | - 28 / - 21 degree        |                              9 |                         2 |                             9 |                 8 |                   7 |                         9 |
| cyanogen chloride | - 6 / 14 degree           |                              8 |                         3 |                             9 |                 9 |                   9 |                         8 |
| cyanogen bromide  | 52 / 62 degree            |                              9 |                         5 |                             8 |                 5 |                   6 |                         8 |
| arsine            | - 117 / - 62 degree       |                              9 |                         3 |                             8 |                 5 |                   9 |                         9 |
| vinyl arsine      | 124 degree (boiling)      |                              7 |                         7 |                             9 |                 8 |                   9 |                         6 |
| phosgene          | - 118 / 8                 |                             10 |                         6 |                             9 |                 5 |                   8 |                         6 |

Question:
How many agents have a melting point below 0 degrees?


id: 240b0d45a41eb8f3b90989092af6da7b
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:
| country        |   year |   total |   hydroelectricity |   wind power | biomass and waste   |   solar |
|:---------------|-------:|--------:|-------------------:|-------------:|:--------------------|--------:|
| china          |   2011 | 797.4   |            687.1   |       73.2   | 34                  |  3      |
| european union |   2010 | 699.3   |            397.7   |      149.1   | 123.3               | 23.1    |
| united states  |   2011 | 520.1   |            325.1   |      119.7   | 56.7                |  1.81   |
| brazil         |   2011 | 459.2   |            424.3   |        2.71  | 32.2                |  0.0002 |
| canada         |   2011 | 399.1   |            372.6   |       19.7   | 6.4                 |  0.43   |
| russia         |   2010 | 166.6   |            163.3   |        0.004 | 2.8                 |  0      |
| india          |   2011 | 162     |            131     |       26     | 4                   |  1      |
| germany        |   2012 | 136.1   |             21.2   |       45.3   | 40.9                | 28      |
| norway         |   2011 | 121.4   |            119.6   |        1.29  | 0.48                |  0.02   |
| japan          |   2011 | 116.4   |             82.5   |        4.35  | 23.1                |  3.8    |
| italy          |   2012 |  89.759 |             43.256 |       13.333 | 9.281 (2010)        | 18.637  |

Question:
In which year did the total energy production of the European Union exceed the total energy production of the United States?


id: dd1027470afe8fe9ce4ed5c40e9bc93f
qtype: NumericalReasoning
label: 2010
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   |
|:-----------------------|:-----------|:------------|:------------|:------------|:------------|
| royal flush            | 250        | 500         | 750         | 1000        | 4000        |
| straight flush         | 60         | 120         | 180         | 240         | 400         |
| four aces              | 400        | 800         | 1200        | 1600        | 2000        |
| four of a kind , 2 - 4 | 100        | 200         | 300         | 400         | 500         |
| four of a kind , 5 - k | 50         | 100         | 150         | 200         | 250         |
| full house             | 8          | 16          | 24          | 32          | 40          |
| flush                  | 5          | 10          | 15          | 20          | 25          |
| straight               | 4          | 8           | 12          | 16          | 20          |
| three of a kind        | 3          | 6           | 9           | 12          | 15          |
| two pair               | 1          | 2           | 3           | 4           | 5           |
| jacks or better        | 1          | 2           | 3           | 4           | 5           |
| theoretical return     | 98.68%     | 98.68%      | 98.68%      | 98.68%      | 99.92%      |

Question:
What is the payout for a "four of a kind, 2-4" hand when betting 3 credits?


id: 0bf3ab8f74244dfca72c5290d44e6f3e
qtype: FactChecking
label: 300
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    |   tropical lows |   tropical cyclones |   severe tropical cyclones | strongest storm   |
|:----------|----------------:|--------------------:|---------------------------:|:------------------|
| 1990 - 91 |              10 |                  10 |                          7 | marian            |
| 1991 - 92 |              11 |                  10 |                          9 | jane - irna       |
| 1992 - 93 |               6 |                   3 |                          1 | oliver            |
| 1993 - 94 |              12 |                  11 |                          7 | theodore          |
| 1994 - 95 |              19 |                   9 |                          6 | chloe             |
| 1995 - 96 |              19 |                  14 |                          9 | olivia            |
| 1996 - 97 |              15 |                  14 |                          3 | pancho            |
| 1997 - 98 |              10 |                   9 |                          3 | tiffany           |
| 1998 - 99 |              21 |                  14 |                          9 | gwenda            |
| 1999 - 00 |              13 |                  12 |                          5 | john / paul       |

Question:
What is the average number of tropical cyclones per season?


id: 29ba53ce7ca43a979263ed36798f62a3
qtype: NumericalReasoning
label: 10.6
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:
|   rank | company                      | country     | industry               |   sales (billion ) |   profits (billion ) | assets (billion )   |   market value (billion ) |
|-------:|:-----------------------------|:------------|:-----------------------|-------------------:|---------------------:|:--------------------|--------------------------:|
|      1 | citigroup                    | usa         | banking                |             108.28 |                17.05 | 1 , 4.10            |                    247.66 |
|      2 | general electric             | usa         | conglomerates          |             152.36 |                16.59 | 750.33              |                    372.14 |
|      3 | american international group | usa         | insurance              |              95.04 |                10.91 | 776.42              |                    173.99 |
|      4 | bank of america              | usa         | banking                |              65.45 |                14.14 | 1110.46             |                    188.77 |
|      5 | hsbc                         | uk          | banking                |              62.97 |                 9.52 | 1031.29             |                    186.74 |
|      6 | exxonmobil                   | usa         | oil & gas              |             263.99 |                25.33 | 195.26              |                    405.25 |
|      7 | royal dutch shell            | netherlands | oil & gas              |             265.19 |                18.54 | 193.83              |                    221.49 |
|      8 | bp                           | uk          | oil & gas              |             285.06 |                15.73 | 191.11              |                    231.88 |
|      9 | ing group                    | netherlands | diversified financials |              92.01 |                 8.1  | 1175.16             |                     68.04 |
|     10 | toyota                       | japan       | automotive             |             165.68 |                11.13 | 211.15              |                    140.89 |

Question:
What is the total sales of the top 3 companies in the 'banking' industry?


id: 394939e9fa1967642597a49620069b78
qtype: NumericalReasoning
label: 236.70
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 | China         |     63 |       46 |       32 |     141 |
|      2 | Great Britain |     35 |       30 |       29 |      94 |
|      3 | Canada        |     28 |       19 |       25 |      72 |
|      4 | United States |     27 |       22 |       39 |      88 |
|      5 | Australia     |     26 |       38 |       36 |     100 |
|      6 | Ukraine       |     24 |       12 |       19 |      55 |
|      7 | Spain         |     20 |       27 |       24 |      71 |
|      8 | Germany       |     19 |       28 |       31 |      78 |
|      9 | France        |     18 |       26 |       30 |      74 |
|     10 | Japan         |     17 |       16 |       20 |      53 |

Question:
Which nation won 30 silver medals in the Olympic Games?


id: 6197fb264f5bffbbaadd753cde55c2e5
qtype: FactChecking
label: Great Britain
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   | team              |   apps |   tries |   goals |   points |
|:-------|:------------------|-------:|--------:|--------:|---------:|
| 2004   | castleford tigers |      3 |       0 |       0 |        0 |
| 2005   | castleford tigers |     29 |      24 |       0 |       96 |
| 2006   | castleford tigers |     27 |       8 |       0 |       32 |
| 2007   | castleford tigers |     20 |      19 |       0 |       76 |
| 2008   | castleford tigers |     22 |      13 |       0 |       52 |
| 2009   | castleford tigers |     30 |      19 |       0 |       76 |
| 2010   | castleford tigers |     22 |      10 |       0 |       40 |
| total  | castleford tigers |    153 |      93 |       0 |      372 |

Question:
What is the average number of appearances (apps) per year by Castleford Tigers from 2005 to 2009?


id: 0c698f73ee431f8e473ef3bda75f5427
qtype: NumericalReasoning
label: 25.6
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:
| place                         |   code |   area (km 2 ) |   population | most spoken language   |
|:------------------------------|-------:|---------------:|-------------:|:-----------------------|
| addo elephant national park   |  20602 |           1.08 |           90 | xhosa                  |
| addo                          |  20601 |           3.21 |         1752 | afrikaans              |
| barsheba                      |  20603 |           0.61 |          517 | xhosa                  |
| bontrug                       |  20604 |           2.33 |         6806 | xhosa                  |
| enon                          |  20605 |           0.4  |          782 | afrikaans              |
| kirkwood                      |  20606 |           3.07 |         2749 | afrikaans              |
| kwazenzele                    |  20607 |           3.62 |         3733 | xhosa                  |
| nomathamsanqa                 |  20608 |           1.53 |         9266 | xhosa                  |
| paterson                      |  20609 |           0.22 |          671 | afrikaans              |
| remainder of the municipality |  20610 |        3491.83 |        15218 | xhosa                  |

Question:
What is the total population of all places where Afrikaans is the most spoken language, and how does it compare to the population of the remainder of the municipality?


id: 6e909081b29bd08e4a7c528b6b5e1d84
qtype: NumericalReasoning
label: 5954，less
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   |   races |   wins |   podiums |   poles |   fastest laps |
|:---------|--------:|-------:|----------:|--------:|---------------:|
| 2003     |      10 |      0 |         0 |       0 |              0 |
| 2003     |       5 |      0 |         0 |       0 |              0 |
| 2004     |      14 |      0 |         0 |       0 |              0 |
| 2005     |      16 |      1 |         2 |       0 |              0 |
| 2006     |      14 |      0 |         0 |       0 |              0 |
| 2007     |      15 |      0 |         0 |       0 |              0 |
| 2008     |      17 |      4 |         9 |       2 |              4 |
| 2009     |      16 |      0 |         2 |       1 |              0 |
| 2010     |      16 |      0 |         0 |       0 |              0 |
| 2011     |      17 |      0 |         0 |       0 |              0 |
| 2012     |      16 |      0 |         0 |       0 |              0 |
| 2013     |      10 |      0 |         0 |       0 |              0 |
| total    |     166 |      5 |        13 |       3 |              4 |

Question:
How many races did the driver participate in during the 2005 season?


id: 10d49252c00b82016f0d0b8bfabae105
qtype: FactChecking
label: 16
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:
| Animal                  | Sex                     | Metabolic rate          | Mean   | Difference from mean       | Squared difference from mean   |
|:------------------------|:------------------------|:------------------------|:-------|:---------------------------|:-------------------------------|
| 1                       | Female                  | 727.7                   | 1285.5 | 557.8                      | 311140.84                      |
| 2                       | Female                  | 1086.5                  | 1285.5 | 199.0                      | 39601.00                       |
| 3                       | Female                  | 1091.0                  | 1285.5 | 194.5                      | 37830.25                       |
| 4                       | Female                  | 1361.3                  | 1285.5 | 75.8                       | 5745.64                        |
| 5                       | Female                  | 1490.5                  | 1285.5 | 205.0                      | 42025.00                       |
| 6                       | Female                  | 1956.1                  | 1285.5 | 670.6                      | 449704.36                      |
| -                       | -                       | -                       | -      | -                          | -                              |
| Mean of metabolic rates | Mean of metabolic rates | Mean of metabolic rates | 1285.5 | Sum of squared differences | 886047.09                      |

Question:
Which animal has the highest metabolic rate among all the females?


id: f51a77d4ffba1aedfe3cc6743ed3e054
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:
|   rank | building                                       | address                   | height   |   storeys |   completed |
|-------:|:-----------------------------------------------|:--------------------------|:---------|----------:|------------:|
|      1 | la renaissance apartments                      | 424 spadina crescent e    | -        |        24 |        1983 |
|      2 | hallmark place                                 | 311 6th ave n             | -        |        27 |        1984 |
|      3 | saskatoon square                               | 410 22nd st e             | -        |        17 |        1979 |
|      4 | the terrace apartments                         | 315 5th ave n             | -        |        22 |        1980 |
|      5 | radisson hotel                                 | 405 20th st e             | -        |        20 |        1983 |
|      6 | the view on fifth (formerly milroy apartments) | 320 5th ave n             | -        |        22 |        1968 |
|      7 | the luther                                     | 1223 temperance st        | -        |        22 |        1978 |
|      8 | marquis towers                                 | 241 5th ave n             | -        |        21 |        1966 |
|      9 | carlton towers                                 | 325 5th ave n             | -        |        21 |        1968 |
|     10 | delta bessborough                              | 601 spadina crescent e    | -        |        10 |        1932 |
|     11 | the tower at midtown (formerly cn tower)       | 201 1st avenue south      | -        |        12 |        1970 |
|     12 | saskatoon towers                               | 125 5th avenue north      | -        |        19 |        1972 |
|     13 | avord towers                                   | 606 spadina crescent east | -        |        14 |        1964 |

Question:
What is the average number of storeys of the top 3 buildings by rank that were completed before 1980?


id: 7ee09fe1d48c37e52e56c6ac5615fb80
qtype: NumericalReasoning
label: 20.3
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 | australia     |      3 |        3 |        5 |      11 |
|      2 | russia        |      3 |        3 |        2 |       8 |
|      3 | italy         |      3 |        1 |        2 |       6 |
|      4 | united states |      2 |        0 |        0 |       2 |
|      5 | germany       |      1 |        2 |        3 |       6 |
|      6 | netherlands   |      1 |        2 |        0 |       3 |
|      7 | belgium       |      1 |        0 |        0 |       1 |
|      7 | spain         |      1 |        0 |        0 |       1 |
|      7 | lithuania     |      1 |        0 |        0 |       1 |
|      7 | norway        |      1 |        0 |        0 |       1 |
|      7 | slovenia      |      1 |        0 |        0 |       1 |
|     12 | france        |      0 |        2 |        2 |       4 |
|     13 | denmark       |      0 |        1 |        1 |       2 |
|     13 | portugal      |      0 |        1 |        1 |       2 |
|     15 | hungary       |      0 |        1 |        0 |       1 |
|     15 | switzerland   |      0 |        1 |        0 |       1 |
|     15 | ukraine       |      0 |        1 |        0 |       1 |
|     18 | new zealand   |      0 |        0 |        1 |       1 |
|     18 | south africa  |      0 |        0 |        1 |       1 |

Question:
Which nation has a higher total medal count, Australia or Russia?


id: ef758cb602e41211846652763d99176e
qtype: NumericalReasoning
label: Australia
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:
| ship name        |   year | length    | width    |   passengers |   vessels | speed   |
|:-----------------|-------:|:----------|:---------|-------------:|----------:|:--------|
| mytilene         |   1973 | 138 , 3 m | 22 , 4 m |        1.73  |       225 | 20      |
| european express |   1974 | 159 , 5 m | 21 , 5 m |        1     |       350 | 23      |
| ionian sky       |   1974 | 164 m     | 24 m     |        1.09  |       600 | 22      |
| theofilos        |   1975 | 149 , 4 m | 23 , 5 m |        1.66  |       433 | 18      |
| taxiarchis       |   1976 | 135 , 8 m | 20 , 6 m |      591     |       392 | 18      |
| aqua jewel       |   2002 | 108 m     | 16 , 6 m |        1.675 |       175 | 18 , 5  |
| aqua maria       |   1975 | 101 , 3 m | 18 m     |      592     |       230 | 17      |
| aqua spirit      |   2000 | 75 m      | 15 m     |      400     |        60 | 17      |

Question:
In which year did the average speed of the vessels increase the most compared to the previous year?


id: 21ed2d8a7cbb07a4ae880fc3fdbe5cbb
qtype: NumericalReasoning
label: 1974
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        |   births (000s) |   deaths |   natural growth | total fertility rate   |
|:------------|----------------:|---------:|-----------------:|:-----------------------|
| 1990        |            0.7  |     0.4  |             0.3  | 1.58                   |
| 1991        |            2.4  |     1.85 |             0.55 | 1.31                   |
| 1992        |            3.4  |     2.7  |             0.7  | 1.33                   |
| 1993        |            4.6  |     3.3  |             1.3  | 1.52                   |
| 1994        |            5.8  |     4    |             1.8  | 1.65                   |
| 1995        |            6.75 |     4.6  |             2.15 | 1.72                   |
| 1996        |            7.5  |     5    |             2.5  | 1.70                   |
| 1997        |            8.2  |     5.4  |             2.8  | 1.71                   |
| 1998        |            8.9  |     5.9  |             3    | 1.71                   |
| 1999        |            9.3  |     6.3  |             3    | 1.63                   |
| 2000        |           10.1  |     6.7  |             3.4  | 1.62                   |
| 2001        |           10.3  |     6.9  |             3.4  | 1.56                   |
| 2002        |           10.6  |     7.2  |             3.4  | 1.55                   |
| 2003        |           11.1  |     7.25 |             3.85 | 1.60                   |
| 2004        |           10.9  |     7.4  |             3.5  | 1.55                   |
| 2005        |           11    |     7.6  |             3.4  | 1.55                   |
| 2006        |           11.2  |     7.6  |             3.6  | na                     |
| 2007        |           10.3  |     7.8  |             2.5  | na                     |
| 2008        |           11.6  |     7.8  |             3.8  | na                     |
| 2009        |           11.7  |     7.6  |             4.1  | na                     |
| 1990 - 2009 |          166.4  |   113.3  |            53.1  | na                     |

Question:
In which year was the natural growth rate significantly different from the average natural growth rate between 1990 and 2000?


id: 19f5fcd6b29df032293fab57a9cd5e91
qtype: NumericalReasoning
label: 1990
Task: Table-QA (source dataset: TableBench)

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

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

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

Question:
In the context of cheerleading competitions, the "Average Skill Score" is calculated as the average of the scores in the basic elements, tumbling, stunts, and tosses/pyramids categories. Which team has the highest Average Skill Score?


id: 8065c33205330460aa2d2afbc1da62b2
qtype: NumericalReasoning
label: school of saint anthony ssa seagulls
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:
If the total mintage of coins from 2002 to 2005 is divided equally among 5 people, how many coins would each person receive?


id: 8bdc298597130f0f71bea7bde0c671d2
qtype: NumericalReasoning
label: 30796.6
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:
| member countries        | population            | area (km square)    | gdp (billion us)     | gdp per capita (us)   |
|:------------------------|:----------------------|:--------------------|:---------------------|:----------------------|
| denmark                 | 5021861               | 43094               | 70.032               | 59928                 |
| ireland                 | 3073200               | 70273               | 21.103               | 39638                 |
| united kingdom          | 56210000              | 244820              | 675.941              | 36728                 |
| accession countries     | 64305061              | 358187              | 767.076              | 11929                 |
| existing members (1973) | 192457106             | 1299536             | 2381396              | 12374                 |
| ec9 (1973)              | 256762167 ( + 33.41%) | 1657723 ( + 25.44%) | 3148.472 ( + 32.21%) | 12262 (0.91%)         |

Question:
GDP per Square Kilometer is calculated as the total GDP of a country divided by its area in square kilometers. Based on this definition, which country has the highest GDP per Square Kilometer?


id: f07268ae170e01fb4f8bb1bd2e7ed14b
qtype: NumericalReasoning
label: united kingdom
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 | Order   |   Quantity | GER Nos.         |
|-------:|:--------|-----------:|:-----------------|
|   1893 | N31     |          1 | 999              |
|   1893 | H33     |         10 | 979–988          |
|   1894 | L33     |         10 | 989–998          |
|   1894 | E34     |         10 | 969–978          |
|   1896 | N37     |         10 | 959–968          |
|   1897 | H40     |         10 | 949–958          |
|   1897 | O41     |         10 | 602–608, 946–948 |
|   1898 | G42     |         10 | 542–551          |
|   1898 | K43     |         10 | 562–571          |

Question:
What is the total quantity of orders placed in the earliest two years represented in the table?


id: e22a374e087942766de36d3bd733f72a
qtype: NumericalReasoning
label: 31
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:
| party                    |   pr seats |   district seats |   total elected 2001 |   total seats |
|:-------------------------|-----------:|-----------------:|---------------------:|--------------:|
| liberal democratic party |         20 |               45 |                   65 |           111 |
| democratic party         |          8 |               18 |                   26 |            59 |
| new komeito party        |          8 |                5 |                   13 |            23 |
| liberal party            |          4 |                2 |                    6 |             8 |
| communist party          |          4 |                1 |                    5 |            20 |
| social democratic party  |          3 |                0 |                    3 |             8 |
| new conservative party   |          1 |                0 |                    1 |             5 |
| others                   |          0 |                2 |                    2 |             2 |
| independents             |          0 |                0 |                    0 |             4 |
| total                    |         48 |               73 |                  121 |           247 |

Question:
What is the total number of PR seats won by all parties combined?


id: e7b71d1c7427df2a8dd74f7b599ff66e
qtype: NumericalReasoning
label: 48
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:
| institution                    | location                       |   founded |   enrollment | nickname     |   varsity sports |   joined |
|:-------------------------------|:-------------------------------|----------:|-------------:|:-------------|-----------------:|---------:|
| college of idaho               | caldwell , idaho (31041)       |      1891 |         1042 | coyotes      |               17 |     1988 |
| concordia university           | portland , oregon (538554)     |      1905 |         3111 | cavaliers    |               13 |     1988 |
| corban university              | salem , oregon (142914)        |      1935 |         1160 | warriors     |               13 |     1988 |
| eastern oregon university      | la grande , oregon (12282)     |      1929 |         3743 | mountaineers |               10 |     1988 |
| the evergreen state college    | olympia , washington (44114)   |      1967 |         4509 | geoducks     |                8 |     1999 |
| northwest university           | kirkland , washington (45814)  |      1934 |         1280 | eagles       |                9 |     1997 |
| northwest christian university | eugene , oregon (142185)       |      1895 |         1290 | beacons      |               12 |     2007 |
| oregon institute of technology | klamath falls , oregon (20840) |      1947 |         3927 | owls         |                9 |     1988 |
| southern oregon university     | ashland , oregon (20406)       |      1882 |         6744 | raiders      |               12 |     1988 |
| warner pacific college         | portland , oregon (538554)     |      1937 |         1333 | knights      |                9 |     1999 |

Question:
Which institution has the highest enrollment?


id: 260a34f57017a544911195cfb1908186
qtype: NumericalReasoning
label: southern oregon university