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language: |
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- en |
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license: apache-2.0 |
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--- |
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### Acknowledgements |
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The PUZZLEQA is scraped from [NPR Sunday Puzzle Official Website](https://www.npr.org/series/4473090/sunday-puzzle) and [NPR Puzzle Synopsis](https://groups.google.com/g/nprpuzzle), |
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made by a group of fans by running a mailing list that distributed questions and answers for each week’s puzzle. |
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The authors of the dataset cleaned the data and made some multiple choice based on the question and answers. |
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### Creation |
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The Multiple Choice Dataset is generated from PUZZLEQA dataset using the following algorithm. |
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1. Read the fr_big_exp.tsv.tsv file |
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2. Group rule-question-answer triples in a given Sunday together (so the rules of each question will be the same) |
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3. For each question, randomly select three other answers from answers on the same Sunday. Shuffle 3 selected answers with the correct answer for the given question to obtain 4 choices for this question. \\ |
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4. identify the correct answer for the given question as the "gold" answer. |
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Recent.tsv is the dataset based on the NPR PUZZLE in 2023. |
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# Citation |
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@inproceedings{zhao2023solving, |
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title={Solving and Generating NPR Sunday Puzzles with Large Language Models}, |
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author={Jingmiao Zhao and Carolyn Jane Anderson}, |
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year={2023}, |
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eprint={2306.12255}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL} |
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} |