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---
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](https://github.com/chaochun/nlu-asdiv-dataset)).

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](https://huggingface.co/collections/MU-NLPC/calc-x-652fee9a6b838fd820055483).


## 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**](https://huggingface.co/collections/MU-NLPC/calc-x-652fee9a6b838fd820055483) - datasets for training Calcformers
- [**Calcformers collection**](https://huggingface.co/collections/MU-NLPC/calcformers-65367392badc497807b3caf5) - calculator-using models we trained and published on HF
- [**Calc-X and Calcformers paper**](https://arxiv.org/abs/2305.15017)
- [**Calc-X and Calcformers repo**](https://github.com/prompteus/calc-x)

Here are links to the original dataset:

- [**original ASDiv dataset and repo**](https://github.com/chaochun/nlu-asdiv-dataset)
- [**original ASDiv paper**](https://aclanthology.org/2020.acl-main.92)


## 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](https://aclanthology.org/2020.acl-main.92), and [Calc-X collection](https://arxiv.org/abs/2305.15017) as follows:

```bibtex
@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",
}
```