metadata

language:
  - en
  - ar
license: mit
size_categories:
  - 1K<n<10K
task_categories:
  - text-generation
tags:
  - math world problems
  - math
  - arithmetics
dataset_info:
  - config_name: default
    features:
      - name: id
        dtype: string
      - name: question
        dtype: string
      - name: chain
        dtype: string
      - name: result
        dtype: string
      - name: result_float
        dtype: float64
      - name: equation
        dtype: string
      - name: expression
        dtype: string
    splits:
      - name: train
        num_bytes: 298347
        num_examples: 1089
      - name: validation
        num_bytes: 285321
        num_examples: 1040
      - name: test
        num_bytes: 142648
        num_examples: 520
    download_size: 0
    dataset_size: 726316
  - config_name: original-splits
    features:
      - name: id
        dtype: string
      - name: question
        dtype: string
      - name: chain
        dtype: string
      - name: result
        dtype: string
      - name: result_float
        dtype: float64
      - name: equation
        dtype: string
      - name: expression
        dtype: string
    splits:
      - name: train
        num_bytes: 1000546
        num_examples: 3636
      - name: test
        num_bytes: 142648
        num_examples: 520
      - name: validation
        num_bytes: 285321
        num_examples: 1040
    download_size: 128730
    dataset_size: 1428515
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: validation
        path: data/validation-*
      - split: test
        path: data/test-*
  - config_name: original-splits
    data_files:
      - split: train
        path: original-splits/train-*
      - split: test
        path: original-splits/test-*
      - split: validation
        path: original-splits/validation-*

Dataset Card for Calc-MAWPS

Summary

The dataset is a collection of simple math word problems focused on arithmetics. It is derived from https://huggingface.co/datasets/omarxadel/MaWPS-ar.

The main addition in this dataset variant is the chain column. It was created by converting the solution to a simple html-like language that can be easily parsed (e.g. by BeautifulSoup). The data contains 3 types of tags:

gadget: A tag whose content is intended to be evaluated by calling an external tool (sympy-based calculator in this case)
output: An output of the external tool
result: The final answer to the mathematical problem (a number)

Supported Tasks

This variant of the dataset is intended for training Chain-of-Thought reasoning models able to use external tools to enhance the factuality of their responses. This dataset presents in-context scenarios where models can outsource the computations in the reasoning chain to a calculator.

Attributes:

id: id of the example
question: problem description in English
question_arabic: problem description in Arabic
chain: series of simple operations (derived from expression) that lead to the solution
result: the solution for x as a number or fraction (string)
result_float: same as result but converted to a float
equation: an equation that needs to be solved for x to obtain the result. Usually in the form of "x = ..." but not always.
expression: arithmetic expression derived from equation that solves it for x

Data splits

We provide 2 variants of the dataset. In the first one, the data splits correspond to the original one and can be loaded using:

datasets.load_dataset("MU-NLPC/calc-mawps", "original-splits")

The second one is filtered to prevent data leaks (overly similar examples in train and test/val splits) in between and across datasets in Calc-X collection. Specifically, we filtered out around 2,500 near-duplicates from the train set that were similar to some instances in the MAWPS val and test splits and ASDiv-A test split. You can load this variant via:

datasets.load_dataset("MU-NLPC/calc-mawps")

Licence

MIT, consistent with the original source dataset linked above.

Related work

If you are interested in related datasets (or models), check out the MU-NLPC organization here on HuggingFace. We have released a few other datasets in a compatible format, and several models that use an external calculator during inference.

Cite

If you use this version of the dataset in research, please cite the original MAWPS paper, and Calc-X paper as follows:

@inproceedings{kadlcik-etal-2023-soft,
    title = "Calc-X and Calcformers: Empowering Arithmetical Chain-of-Thought through Interaction with Symbolic Systems",
    author = "Marek Kadlčík and Michal Štefánik and Ondřej Sotolář and Vlastimil Martinek",
    booktitle = "Proceedings of the The 2023 Conference on Empirical Methods in Natural Language Processing: Main track",
    month = december,
    year = "2023",
    address = "Singapore, Singapore",
    publisher = "Association for Computational Linguistics",
    url = "https://arxiv.org/abs/2305.15017",
}