README.md

metadata

language:
  - en
license: apache-2.0
tags:
  - text
  - question-and-answer
pretty_name: AQuA-Rat
task_categories:
  - question-answering

Dataset Card for AQuA-Rat

• Homepage: https://github.com/google-deepmind/AQuA
  • This is an unofficial curation of the AQuA-Rat dataset, uploaded here with minimal (i.e., no content-modifying) processing.
• Paper: Program Induction by Rationale Generation: Learning to Solve and Explain Algebraic Word Problems (ACL Anthology)

Modifications:

• Pre-tokenized splits removed since tokenization built into most LM pipelines.
• Fixed file suffix from .json to .jsonl.
• Changed options column to hardcoded A-E columns for easier parsing.
• Changed correct column name to answer_idx and added answer containing the text of the correct answer.

Dataset Structure

Column names have been slightly modified from the original dataset:

question: The question/prompt.
rationale: The explanation for the solution.
A: The "A" answer.
B: The "B" answer.
C: The "C" answer.
D: The "D" answer.
E: The "E" answer.
answer_idx: The multiple-choice identifier for the correct answer.
answer: The correct answer.

Compare this example with its equivalent from the original dataset.

New:

{
  "question": "Find out which of the following values is the multiple of X, if it is divisible by 9 and 12?",
  "rationale": "9=3*3\n12=3*4\nThe number should definitely have these factors 3*3*4\n36 is the number that has these factors\nSo, 36 is the multiple of X\nAnswer is A",
  "A": "36",
  "B": "15",
  "C": "17",
  "D": "5",
  "E": "7",
  "answer_idx": "A",
  "answer": "36"
}

Original:

{
  "question": "Find out which of the following values is the multiple of X, if it is divisible by 9 and 12?",
  "options": ["A)36", "B)15", "C)17", "D)5", "E)7"],
  "rationale": "9=3*3\n12=3*4\nThe number should definitely have these factors 3*3*4\n36 is the number that has these factors\nSo, 36 is the multiple of X\nAnswer is A",
  "correct": "A",
}

No other changes were made.

Citation Information

For reproducibility, please include a link to this dataset when publishing results based on the included data.

For formal citations, please cite the original publication:

@inproceedings{ling-etal-2017-program,
    title = "Program Induction by Rationale Generation: Learning to Solve and Explain Algebraic Word Problems",
    author = "Ling, Wang and Yogatama, Dani and Dyer, Chris and Blunsom, Phil",
    editor = "Barzilay, Regina and Kan, Min-Yen",
    booktitle = "Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
    month = jul,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/P17-1015/",
    doi = "10.18653/v1/P17-1015",
    pages = "158--167"
}