task_categories:text-generation task_categories:question-answering size_categories:1K<n<10K language:en license:mit arxiv:2110.14168 arxiv:2305.15017 region:us
---
license: mit
task_categories:
- text-generation
- question-answering
language:
- en
size_categories:
- 1K<n<10K
---
# Dataset Card for "Calc-gsm8k"


## Summary

This dataset is an instance of gsm8k dataset, converted 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 of the mathematical problem (a number)


## Supported Tasks

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 out-source the computations in the reasoning chain to a calculator.


## Construction Process

The answers in the original dataset was in in a structured but non-standard format. So, the answers were parsed, all arithmetical expressions
were evaluated using a sympy-based calculator, the outputs were checked to be consistent with the intermediate results and finally exported
into a simple html-like language that BeautifulSoup can parse.


## Content and Data splits

Content and splits correspond to the original gsm8k dataset.
See [gsm8k HF dataset](https://huggingface.co/datasets/gsm8k) and [official repository](https://github.com/openai/grade-school-math) for more info.


## Licence

MIT, consistently with the original dataset.


## Cite

If you use this version of dataset in research, please cite the [original GSM8K paper](https://arxiv.org/abs/2110.14168) and our report as follows:

```bibtex
@article{kadlcik2023calcx,
         title={Calc-X: Enriching Arithmetical Chain-of-Thoughts Datasets by Interaction with Symbolic Systems}, 
         author={Marek Kadlčík and Michal Štefánik},
         year={2023},
         eprint={2305.15017},
         archivePrefix={arXiv},
         primaryClass={cs.LG}
}
```