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license: cc-by-nc-sa-4.0 |
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# Mystery Zebra Dataset |
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This is the Mystery Zebra dataset created as part of the paper "Lexical Recall or Logical Reasoning: Probing the Limits of Reasoning Abilities in Large Language Models". We make the dataset available in a .csv format for your convenience. The code used to generate the puzzles in this dataset can be found in: https://github.com/arg-tech/MysteryZebra The structure of the dataset is straightforward and easy to parse. In the following, we detail the content of all the columns in the .csv file: |
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- __ID__: This field contains the ID of the datapoint. |
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- For puzzles of the first part of the benchmark it is composed as follows: Pt1_Einstein_1domain_replacements-0, indicating: |
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- ```<Part_of_benchmark>_<classic_puzzle_name>_<obfuscation_type>-<running_number>``` |
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- For puzzles of the second part of the benchmark it is composed as follows: Pt2_1x6_level1-0, indicating: |
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- ```<part_of_benchmark>_<columns x rows>_<level>-<running_number>``` |
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- __Clues__: This field contains the set of clues given to solve the puzzle. This is written out in Natural Language. |
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- For any puzzle that is not a `Zebra_original`or an `Einstein_original'. this is in the uniform phrasing detailed in our paper. |
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- __SolutionGrid__: This field contains the correct solution grid for the puzzle in the form of a phyton dictionary, where the keys correspont to a domain name (e.g. pets) and the items are in an ordered list, where indices equal positions in the grid. |
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## Referencing |
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Please reference the corpus as follows: |
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[INSERT BIB INFO ONCE THERE] |
