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 | class   | team   |   points | rank   |   wins |
|-------:|:--------|:-------|---------:|:-------|-------:|
|   1994 | 125cc   | honda  |       24 | 20th   |      0 |
|   1995 | 125cc   | honda  |      102 | 8th    |      0 |
|   1996 | 125cc   | honda  |      167 | 3rd    |      1 |
|   1997 | 125cc   | honda  |      190 | 3rd    |      0 |
|   1998 | 125cc   | honda  |      217 | 2nd    |      5 |
|   1999 | 250cc   | yamaha |       52 | 15th   |      0 |

Question:
What is the average annual increase in points from 1994 to 1998 for the 'honda' team in the '125cc' class?


id: 74a141ffb44ab78e143b3824b352eee2
qtype: NumericalReasoning
label: 48.25
Task: Table-QA (source dataset: TableBench)

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

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

Table:
|   rd |   pick | player          | team (league)                           |   reg gp |   pl gp |
|-----:|-------:|:----------------|:----------------------------------------|---------:|--------:|
|    2 |     23 | ron sedlbauer   | kitchener rangers ( oha )               |      325 |      10 |
|    3 |     41 | john hughes     | toronto marlboros ( oha )               |       52 |       4 |
|    4 |     59 | harold snepsts  | edmonton oil kings ( wchl )             |      781 |      44 |
|    5 |     77 | mike rogers     | calgary centennials ( wchl )            |        0 |       0 |
|    6 |     95 | andy spruce     | london knights ( oha )                  |       51 |       0 |
|    7 |    113 | jim clarke      | toronto marlboros ( oha )               |        0 |       0 |
|    8 |    130 | robbie watt     | flin flon bombers ( wchl )              |        0 |       0 |
|    9 |    147 | marc gaudreault | lake superior state university ( ncaa ) |        0 |       0 |

Question:
If the average number of regular season games played ('reg gp') by a player is 300, how many more games did Harold Snepsts play than the average?


id: ac040e9638b60682e8102d7bcfc4a8f7
qtype: NumericalReasoning
label: 481
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:
| language           |   totora municipality |   pojo municipality |   pocona municipality |   chimoré municipality |   puerto villarroel municipality |   entre ríos municipality |
|:-------------------|----------------------:|--------------------:|----------------------:|-----------------------:|---------------------------------:|--------------------------:|
| quechua            |                 11671 |               10203 |                 12482 |                   9596 |                            29940 |                     14789 |
| aymara             |                    72 |                  74 |                    39 |                    965 |                             1590 |                       907 |
| guaraní            |                     7 |                   9 |                     3 |                     19 |                               39 |                        41 |
| another native     |                    16 |                   9 |                     6 |                    424 |                              235 |                        27 |
| spanish            |                  4967 |                4991 |                  4954 |                  11530 |                            29377 |                     17164 |
| foreign            |                    32 |                  15 |                    22 |                    128 |                              199 |                       142 |
| only native        |                  7060 |                5623 |                  7706 |                   2518 |                             8131 |                      3207 |
| native and spanish |                  4645 |                4598 |                  4790 |                   7811 |                            22426 |                     11864 |
| only spanish       |                   322 |                 393 |                   166 |                   3726 |                             6956 |                      5314 |

Question:
Which municipality has the highest population of Spanish speakers?


id: 9ea49f48f21f83149313285053b6621c
qtype: NumericalReasoning
label: puerto villarroel municipality
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        |      3 |        5 |        4 |      12 |
| 2      | hungary        |      6 |        1 |        4 |      11 |
| 3      | poland         |      3 |        4 |        3 |      10 |
| 4      | spain          |      2 |        2 |        3 |       7 |
| 5      | russia         |      3 |        2 |        1 |       6 |
| 6      | canada         |      0 |        3 |        2 |       5 |
| 7      | romania        |      1 |        1 |        2 |       4 |
| 8      | slovakia       |      3 |        0 |        0 |       3 |
| 9      | cuba           |      2 |        1 |        0 |       3 |
| 10     | bulgaria       |      0 |        1 |        2 |       3 |
| 11     | norway         |      1 |        1 |        0 |       2 |
| 12     | lithuania      |      1 |        0 |        1 |       2 |
| 13     | czech republic |      0 |        2 |        0 |       2 |
| 14     | belarus        |      0 |        1 |        1 |       2 |
| 15     | uzbekistan     |      0 |        1 |        1 |       2 |
| 16     | italy          |      0 |        0 |        2 |       2 |
| 17     | australia      |      1 |        0 |        0 |       1 |
| 18     | sweden         |      1 |        0 |        0 |       1 |
| 19     | argentina      |      0 |        1 |        0 |       1 |
| 20     | china          |      0 |        1 |        0 |       1 |
| 21     | ukraine        |      0 |        1 |        0 |       1 |
| 22     | israel         |      0 |        0 |        1 |       1 |
| total  | total          |     27 |       27 |       27 |      81 |

Question:
Which nation ranked with a total of 6 medals?


id: 73cc123cf088d1762671001ecd08190f
qtype: FactChecking
label: russia
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 |   typhus |   typhoid fever |   relapsing fever |   smallpox | malaria    |
|-------:|---------:|----------------:|------------------:|-----------:|:-----------|
|   1913 |      120 |             424 |                30 |         67 | 3600       |
| 191822 |     1300 |             293 |               639 |        106 | 2940 (avg) |
|   1929 |       40 |             170 |                 6 |          8 | 3000       |
|   1930 |       60 |             190 |                 5 |         10 | 2700       |
|   1931 |       80 |             260 |                 4 |         30 | 3200       |
|   1932 |      220 |             300 |                12 |         80 | 4500       |
|   1933 |      800 |             210 |                12 |         38 | 6500       |
|   1934 |      410 |             200 |                10 |         16 | 9477       |
|   1935 |      120 |             140 |                 6 |          4 | 9924       |

Question:
In which year did the number of typhus cases decrease the most compared to the previous year?


id: e9e9a6d74cf7166df1967b0f0a2980ae
qtype: NumericalReasoning
label: 1929
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                             | height       |   floors |   completed |
|-------:|:-------------------------------------|:-------------|---------:|------------:|
|      1 | fenwick tower (residential)          | 98 m (322ft) |       32 |        1971 |
|      2 | purdy 's wharf tower 2 (office)      | 88 m (289ft) |       22 |        1990 |
|      3 | 1801 hollis street (office)          | 87 m (285ft) |       22 |        1985 |
|      4 | barrington tower (office)            | 84 m (276ft) |       20 |        1975 |
|      5 | cogswell tower (office)              | 79 m (259ft) |       20 |        1975 |
|      6 | maritime centre (office)             | 78 m (256ft) |       21 |        1974 |
|      7 | queen square (office)                | 75 m (246ft) |       19 |        1975 |
|      8 | purdy 's wharf tower 1 (office)      | 74 m (243ft) |       18 |        1985 |
|      9 | bank of montreal building (office)   | 73 m (240ft) |       18 |        1971 |
|     10 | td tower (office)                    | 73 m (240ft) |       18 |        1974 |
|     11 | duke tower (office)                  | 71 m (233ft) |       16 |        1970 |
|     12 | founders square (office)             | 71 m (233ft) |       15 |        1970 |
|     13 | tupper building (educational)        | 70 m (233ft) |       16 |        1967 |
|     14 | park victoria (residential)          | 70 m (233ft) |       21 |        1969 |
|     15 | summer gardens (residential)         | 70 m (233ft) |       21 |        1990 |
|     16 | loyola residence tower (residential) | 67 m (220ft) |       22 |        1971 |
|     17 | metropolitan place (office)          | 67 m (218ft) |       16 |        1987 |
|     18 | bank of commerce (office)            | 66 m (217ft) |       16 |        1977 |
|     19 | the trillium (residential)           | 65 m (213ft) |       19 |        2011 |

Question:
If the average height of the top 5 buildings is increased by 5 meters, what would be the new average height?


id: 234c6edbcd38217533fb4463d944bf90
qtype: NumericalReasoning
label: 92.2
Task: Table-QA (source dataset: TableBench)

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

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

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

Question:
What is the total population of the top 5 cities in the table?


id: 1274eebbc02e9c74547f94c43fbd5cdb
qtype: NumericalReasoning
label: 206713
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:
| fuel gas     |   upper index kcal / nm 3 |   lower index kcal / nm 3 |   upper index mj / nm 3 |   lower index mj / nm 3 |
|:-------------|--------------------------:|--------------------------:|------------------------:|------------------------:|
| hydrogen     |                     11528 |                      9715 |                   48.23 |                   40.65 |
| methane      |                     12735 |                     11452 |                   53.28 |                   47.91 |
| ethane       |                     16298 |                     14931 |                   68.19 |                   62.47 |
| ethylene     |                     15253 |                     14344 |                   63.82 |                   60.01 |
| natural gas  |                     12837 |                     11597 |                   53.71 |                   48.52 |
| propane      |                     19376 |                     17817 |                   81.07 |                   74.54 |
| propylene    |                     18413 |                     17180 |                   77.04 |                   71.88 |
| n - butane   |                     22066 |                     20336 |                   92.32 |                   85.08 |
| iso - butane |                     21980 |                     20247 |                   91.96 |                   84.71 |
| butylene - 1 |                     21142 |                     19728 |                   88.46 |                   82.54 |
| lpg          |                     20755 |                     19106 |                   86.84 |                   79.94 |
| acetylene    |                     14655 |                     14141 |                   61.32 |                   59.16 |

Question:
What is the difference between the upper index kcal/nm³ of propane and the lower index kcal/nm³ of propane?


id: 432da69c8bf6e4c02ea05c70a4369a81
qtype: NumericalReasoning
label: 1559
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:
|   position | team             |   played |   wins |   draws |   losses |   scored |   conceded |   points |
|-----------:|:-----------------|---------:|-------:|--------:|---------:|---------:|-----------:|---------:|
|          1 | cerro porteño    |        9 |      5 |       2 |        2 |       14 |          7 |       17 |
|          2 | libertad         |        9 |      4 |       4 |        1 |       12 |          4 |       16 |
|          3 | 12 de octubre    |        9 |      5 |       1 |        3 |       15 |         10 |       16 |
|          4 | cerro corá       |        9 |      4 |       2 |        3 |       15 |         14 |       14 |
|          5 | san lorenzo      |        9 |      4 |       1 |        4 |       11 |         11 |       13 |
|          6 | sportivo luqueño |        9 |      3 |       4 |        2 |       11 |         12 |       13 |
|          7 | guaraní          |        9 |      3 |       1 |        5 |        6 |          9 |       10 |
|          8 | sol de américa   |        9 |      2 |       3 |        4 |       11 |         16 |        9 |
|          9 | atl colegiales   |        9 |      2 |       3 |        4 |        6 |         11 |        9 |

Question:
Which team is currently in 3rd position in the league?


id: b706776a23c7b8fc4d8036047a48890e
qtype: FactChecking
label: 12 de octubre
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:
What is the difference in enrollment between the institution with the highest enrollment and the institution with the lowest enrollment?


id: 447813cef258e268820b0788458283ad
qtype: NumericalReasoning
label: 5,702
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 | United States (USA)       |     25 |       16 |        7 |      48 |
|      2 | Canada (CAN)              |      5 |        4 |        7 |      16 |
|      3 | Jamaica (JAM)             |      4 |        3 |        4 |      11 |
|      4 | Cuba (CUB)                |      3 |        8 |        4 |      15 |
|      5 | Mexico (MEX)              |      0 |        3 |        3 |       6 |
|      6 | Brazil (BRA)              |      0 |        2 |        1 |       3 |
|      7 | Puerto Rico (PUR)         |      0 |        1 |        1 |       2 |
|      8 | Colombia (COL)            |      0 |        0 |        3 |       3 |
|      9 | Peru (PER)                |      0 |        0 |        2 |       2 |
|      9 | Trinidad and Tobago (TRI) |      0 |        0 |        2 |       2 |
|     11 | Chile (CHI)               |      0 |        0 |        1 |       1 |
|     11 | Uruguay (URU)             |      0 |        0 |        1 |       1 |
|     11 | Venezuela (VEN)           |      0 |        0 |        1 |       1 |

Question:
According to the table, which nation won 4 gold medals and 3 silver medals?


id: db5d51a82497e56cdd5c4b55ba02f07b
qtype: FactChecking
label: Jamaica (JAM)
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           |   2010 |   2009 |   2008 |   2005 |   2000 |
|:---------------|-------:|-------:|-------:|-------:|-------:|
| shanghai       |      1 |      2 |      1 |      1 |      1 |
| beijing        |      2 |      1 |      2 |      2 |      2 |
| tianjin        |      3 |      3 |      3 |      3 |      3 |
| jiangsu        |      4 |      4 |      5 |      6 |      6 |
| zhejiang       |      5 |      5 |      4 |      4 |      4 |
| inner mongolia |      6 |      6 |      7 |     10 |     15 |
| guangdong      |      7 |      7 |      6 |      5 |      5 |
| liaoning       |      8 |      9 |      9 |      8 |      8 |
| shandong       |      9 |      8 |      8 |      7 |      9 |
| fujian         |     10 |     10 |     10 |      9 |      7 |
| jilin          |     11 |     11 |     11 |     13 |     13 |
| hebei          |     12 |     12 |     12 |     11 |     11 |
| hubei          |     13 |     14 |     16 |     17 |     16 |
| chongqing      |     14 |     13 |     15 |     16 |     17 |
| shaanxi        |     15 |     16 |     18 |     20 |     23 |
| heilongjiang   |     16 |     15 |     13 |     12 |     10 |
| ningxia        |     17 |     17 |     19 |     22 |     21 |
| shanxi         |     18 |     18 |     14 |     15 |     18 |
| xinjiang       |     19 |     21 |     17 |     14 |     12 |
| hunan          |     20 |     20 |     22 |     21 |     20 |
| henan          |     21 |     19 |     20 |     18 |     19 |
| qinghai        |     22 |     22 |     21 |     23 |     22 |
| hainan         |     23 |     23 |     23 |     19 |     14 |
| jiangxi        |     24 |     25 |     24 |     24 |     25 |
| sichuan        |     25 |     24 |     25 |     25 |     24 |
| anhui          |     26 |     26 |     27 |     27 |     26 |
| guangxi        |     27 |     27 |     26 |     28 |     28 |
| tibet          |     28 |     28 |     28 |     26 |     29 |
| gansu          |     29 |     30 |     30 |     30 |     30 |
| yunnan         |     30 |     29 |     29 |     29 |     27 |
| guizhou        |     31 |     31 |     31 |     31 |     31 |

Question:
What was the ranking of guangdong in 2008?


id: ee38d1e26018264f906e82e45b85e4d8
qtype: FactChecking
label: 6
Task: Table-QA (source dataset: TableBench)

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

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

Table:
|   Year |   Conservative |        Labour |   Independent |       Liberal |
|        |    councillors |   councillors |   councillors |   councillors |
|-------:|---------------:|--------------:|--------------:|--------------:|
|   1947 |              3 |             2 |            18 |             1 |
|   1951 |              5 |             2 |            17 |             0 |
|   1952 |              3 |             3 |            18 |             0 |
|   1953 |              4 |             3 |            17 |             0 |
|   1954 |              3 |             4 |            17 |             0 |
|   1955 |              2 |             5 |            17 |             0 |
|   1956 |              2 |             6 |            16 |             0 |
|   1957 |              2 |             5 |            17 |             0 |
|   1958 |              2 |             6 |            16 |             0 |
|   1960 |              2 |             5 |            16 |             1 |
|   1961 |              2 |             5 |            15 |             2 |
|   1963 |              2 |             6 |            12 |             4 |
|   1964 |              3 |             6 |            11 |             4 |
|   1965 |              4 |             5 |            11 |             3 |
|   1966 |              9 |             4 |             6 |             5 |
|   1967 |              9 |             4 |             9 |             2 |
|   1972 |             10 |            10 |             3 |             1 |

Question:
In which year did the number of Conservative councillors increase the most compared to the previous year?


id: 13daefeaa77341d83862c3671bc59d42
qtype: NumericalReasoning
label: 1966
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 tropical storms |   number of hurricanes |   number of major hurricanes | deaths    | strongest storm   |
|-------:|----------------------------:|-----------------------:|-----------------------------:|:----------|:------------------|
|   1850 |                           0 |                      3 |                            0 | not known | one               |
|   1851 |                           6 |                      3 |                            1 | 24        | four              |
|   1852 |                           5 |                      5 |                            1 | 100 +     | one               |
|   1853 |                           8 |                      4 |                            2 | 40        | three             |
|   1854 |                           5 |                      3 |                            1 | 30 +      | three             |
|   1855 |                           5 |                      4 |                            1 | not known | five              |
|   1856 |                           6 |                      4 |                            2 | 200 +     | one               |
|   1857 |                           4 |                      3 |                            0 | 424       | two & four        |
|   1858 |                           6 |                      6 |                            0 | none      | three & six       |

Question:
What is the average number of tropical storms per year from 1850 to 1855?


id: 1c2ac440f5591f15c8ff60fe1644335a
qtype: NumericalReasoning
label: 4.83
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:
| index                         | organization                         |     year |   rank |   out of |
|:------------------------------|:-------------------------------------|---------:|-------:|---------:|
| bribe payers index            | transparency international           |     2011 |     19 |       28 |
| corruption perceptions index  | transparency international           |     2012 |     37 |      176 |
| democracy index               | economist intelligence unit          |     2010 |     36 |      167 |
| ease of doing business index  | world bank                           |     2012 |     16 |      185 |
| economic freedom index        | fraser institute                     |     2010 |     15 |      144 |
| economic freedom index        | the heritage foundation              |     2013 |     20 |      177 |
| global competitiveness report | world economic forum                 | 20122013 |     13 |      144 |
| global peace index            | institute for economics and peace    |     2011 |     27 |      153 |
| globalization index           | at kearney / foreign policy magazine |     2006 |     35 |       62 |
| press freedom index           | reporters without borders            |     2013 |     47 |      179 |
| property rights index         | property rights alliance             |     2008 |     28 |      115 |

Question:
What is the average rank of the indices published by Transparency International?


id: 9f6acb3e258123c6d0841b052d95505f
qtype: NumericalReasoning
label: 28
Task: Table-QA (source dataset: TableBench)

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

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

Table:
| player            |   matches |   innings |   runs |   average |   highest score |   100s |   50s |
|:------------------|----------:|----------:|-------:|----------:|----------------:|-------:|------:|
| lionel palairet   |        10 |        19 |    560 |     31.11 |             100 |      1 |     5 |
| john challen      |         9 |        16 |    354 |     25.28 |              89 |      0 |     2 |
| richard palairet  |        10 |        17 |    266 |     19    |              74 |      0 |     1 |
| herbie hewett     |        12 |        22 |    388 |     18.47 |              65 |      0 |     2 |
| sammy woods       |        11 |        19 |    330 |     18.33 |              50 |      0 |     1 |
| bill roe          |         7 |        12 |    168 |     15.27 |              36 |      0 |     0 |
| crescens robinson |        11 |        17 |    196 |     14    |              55 |      0 |     1 |
| vernon hill       |         9 |        15 |    184 |     12.26 |              31 |      0 |     0 |
| george nichols    |        12 |        21 |    216 |     10.28 |              37 |      0 |     0 |
| ted tyler         |        12 |        20 |    168 |      9.88 |              62 |      0 |     1 |

Question:
What is the highest score achieved by Lionel Palairet in his cricket career?


id: 9280930f516f9e7e740df6336b2c327a
qtype: FactChecking
label: 100
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:
| crime               |   reported offenses |   killeen rate |   texas rate |   us rate |
|:--------------------|--------------------:|---------------:|-------------:|----------:|
| murder              |                  10 |            8.6 |          5.6 |       5.6 |
| rape                |                  66 |           56.9 |         32.9 |      29.4 |
| robbery             |                 216 |          186.4 |        155.2 |     154   |
| aggravated assault  |                 593 |          511.6 |        314.4 |     281.6 |
| violent crime       |                 885 |          763.5 |        508.2 |     470.6 |
| burglary            |                1711 |         1476.2 |        946.5 |     743.4 |
| larceny - theft     |                2877 |         2482.2 |       2688.9 |    2200.1 |
| motor vehicle theft |                 169 |          145.8 |        351.1 |     330.5 |
| non - violent crime |                4757 |         4104.2 |       3986.6 |    3274   |

Question:
How many more reported offenses of 'larceny - theft' were there compared to 'burglary'?


id: 876647763592d2d08384449540eb212d
qtype: NumericalReasoning
label: 1166
Task: Table-QA (source dataset: TableBench)

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

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

Table:
| election   | dã¡il   | share of votes   |   seats |   total seats |
|:-----------|:--------|:-----------------|--------:|--------------:|
| 1927 (jun) | 5th     | 26.2%            |      44 |           153 |
| 1927 (sep) | 6th     | 35.2%            |      57 |           153 |
| 1932       | 7th     | 44.5%            |      72 |           153 |
| 1933       | 8th     | 49.7%            |      76 |           153 |
| 1937       | 9th     | 45.2%            |      68 |           138 |
| 1938       | 10th    | 51.9%            |      76 |           138 |
| 1943       | 11th    | 41.8%            |      66 |           138 |
| 1944       | 12th    | 48.9%            |      75 |           138 |
| 1948       | 13th    | 41.9%            |      67 |           147 |
| 1951       | 14th    | 46.3%            |      68 |           147 |
| 1954       | 15th    | 43.4%            |      65 |           147 |
| 1957       | 16th    | 48.3%            |      78 |           147 |
| 1961       | 17th    | 43.8%            |      70 |           144 |
| 1965       | 18th    | 47.7%            |      72 |           144 |
| 1969       | 19th    | 44.6%            |      74 |           144 |
| 1973       | 20th    | 46.2%            |      68 |           144 |
| 1977       | 21st    | 50.6%            |      84 |           148 |
| 1981       | 22nd    | 45.3%            |      77 |           166 |
| 1982 (feb) | 23rd    | 47.3%            |      81 |           166 |
| 1982 (nov) | 24th    | 45.2%            |      75 |           166 |
| 1987       | 25th    | 44.2%            |      81 |           166 |
| 1989       | 26th    | 44.2%            |      77 |           166 |
| 1992       | 27th    | 39.1%            |      68 |           166 |
| 1997       | 28th    | 39.3%            |      77 |           166 |
| 2002       | 29th    | 41.5%            |      81 |           166 |
| 2007       | 30th    | 41.6%            |      77 |           166 |
| 2011       | 31st    | 17.4%            |      20 |           166 |

Question:
How many elections did the party win75 or more seats?


id: 66ea61b936831554ebaa4423d2600550
qtype: NumericalReasoning
label: 13
Task: Table-QA (source dataset: TableBench)

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

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

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

Question:
In which year did the team experience the largest increase in the number of wins compared to the previous year?


id: 3f6993cc9f6540e04eaba1d69d6d69b6
qtype: NumericalReasoning
label: 2012