README.md

metadata

license: apache-2.0
task_categories:
  - question-answering
  - multiple-choice
language:
  - en
tags:
  - mathematics
  - algebra
  - word-problems
  - mcqa
  - reasoning
size_categories:
  - 10K<n<100K

AQUA-RAT MCQA Dataset

This dataset contains the AQUA-RAT dataset converted to Multiple Choice Question Answering (MCQA) format with modifications.

Dataset Description

AQUA-RAT is a dataset of algebraic word problems with rationales. This version has been processed to:

• Remove all questions where the correct answer was option "E" (5th choice)
• Remove the "E" option from all remaining questions (4 choices: A, B, C, D)
• Merge validation and test splits into a single test split

Dataset Structure

Each example contains:

• question: The algebraic word problem
• choices: List of 4 possible answers (A, B, C, D)
• answer_index: Index of the correct answer (0-3)
• answer_text: Text of the correct answer
• source: Dataset source ("aqua_rat")
• explanation: Detailed rationale/solution

Data Splits

• Train: 83671 examples
• Test: 448 examples (merged validation + test)

Usage

from datasets import load_dataset

dataset = load_dataset("RikoteMaster/aqua-rat-mcqa")

Original Dataset

This dataset is based on the AQUA-RAT dataset:

• Paper: https://arxiv.org/abs/1705.04146
• Original repository: https://huggingface.co/datasets/deepmind/aqua_rat

Citation

@misc{ling2017program,
    title={Program Induction by Rationale Generation: Learning to Solve and Explain Algebraic Word Problems}, 
    author={Wang Ling and Dani Yogatama and Chris Dyer and Phil Blunsom},
    year={2017},
    eprint={1705.04146},
    archivePrefix={arXiv},
    primaryClass={cs.CL}
}