metadata

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: result_unit
        dtype: string
      - name: grade
        dtype: int64
      - name: source_question
        dtype: string
    splits:
      - name: test
        num_bytes: 415636
        num_examples: 1218
    download_size: 152949
    dataset_size: 415636
  - 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: result_unit
        dtype: string
      - name: grade
        dtype: int64
      - name: source_question
        dtype: string
    splits:
      - name: test
        num_bytes: 415664
        num_examples: 1218
    download_size: 152949
    dataset_size: 415664
configs:
  - config_name: default
    data_files:
      - split: test
        path: data/test-*
  - config_name: original-splits
    data_files:
      - split: test
        path: original-splits/test-*

Dataset Card for Calc-asdiv_a

Summary

The dataset is a collection of simple math word problems focused on arithmetics. It is derived from the arithmetic subset of ASDiv (original repo).

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.

Data splits

The dataset does not contain data splits. We consider the whole dataset as a testing benchmark.

Attributes:

id: id of the example
question problem description in English
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
result_unit: the units of the result
grade: an estimate of the school grade in which the problem would be practiced
source_question: the source from which the example originates

Attributes id, question, chain, and result are present in all datasets in the Calc-X collection.

Related work

This dataset was created as a part of a larger effort in training models capable of using a calculator during inference, which we call Calcformers.

Calc-X collection - datasets for training Calcformers
Calcformers collection - calculator-using models we trained and published on HF
Calc-X and Calcformers paper
Calc-X and Calcformers repo

Here are links to the original dataset:

Licence

CC BY-NC 4.0, consistent with the original source dataset linked above.

Cite

If you use this dataset in research, please cite the original ASDiv paper, and Calc-X collection 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 = dec,
    year = "2023",
    address = "Singapore, Singapore",
    publisher = "Association for Computational Linguistics",
    url = "https://arxiv.org/abs/2305.15017",
}