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## Summary
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The dataset is a collection of simple math
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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
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parsed (e.g. by BeautifulSoup). The data contains 3 types of tags:
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- gadget: A tag whose content is intended to be evaluated by calling an external tool (sympy-based calculator in this case)
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- output: An output of the external tool
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- result: The final answer
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##
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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.
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This dataset presents in-context scenarios where models can
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## Attributes:
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- `question`: problem description in English
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- `question_arabic`: problem description in Arabic
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- `chain`: series of simple operations (derived from `expression`) that lead to the solution
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- `result`: the solution for x as a number or fraction (string)
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- `result_float`: same as `result` but converted to a float
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- `equation`: equation that needs to be solved for `x` to obtain the result. Usually in
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- `expression`: arithmetic expression derived from `equation` that solves it for `x`
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##
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Both are consistent with the original source dataset.
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## Licence
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## Related work
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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 external calculator during inference.
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## Cite
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If you use this version of dataset in research, please cite the original [MAWPS paper](https://aclanthology.org/N16-1136/) and [Calc-X
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```bibtex
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@inproceedings{kadlcik-etal-2023-soft,
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## Summary
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The dataset is a collection of simple math word problems focused on arithmetics. It is derived from <https://huggingface.co/datasets/omarxadel/MaWPS-ar>.
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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
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parsed (e.g. by BeautifulSoup). The data contains 3 types of tags:
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- gadget: A tag whose content is intended to be evaluated by calling an external tool (sympy-based calculator in this case)
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- output: An output of the external tool
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- result: The final answer to the mathematical problem (a number)
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## Supported Tasks
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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.
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This dataset presents in-context scenarios where models can outsource the computations in the reasoning chain to a calculator.
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## Attributes:
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- `id`: id of the example
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- `question`: problem description in English
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- `question_arabic`: problem description in Arabic
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- `chain`: series of simple operations (derived from `expression`) that lead to the solution
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- `result`: the solution for x as a number or fraction (string)
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- `result_float`: same as `result` but converted to a float
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- `equation`: an equation that needs to be solved for `x` to obtain the result. Usually in the form of "x = ..." but not always.
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- `expression`: arithmetic expression derived from `equation` that solves it for `x`
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## Data splits
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We provide 2 variants of the dataset. In the first one, the data splits correspond to the original one and can be loaded using:
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```python3
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datasets.load_dataset("MU-NLPC/calc-mawps", "original-splits")
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```
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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](https://huggingface.co/collections/MU-NLPC/calc-x-652fee9a6b838fd820055483).
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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:
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```python3
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datasets.load_dataset("MU-NLPC/calc-mawps")
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```
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## Licence
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## Related work
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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.
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## Cite
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If you use this version of the dataset in research, please cite the original [MAWPS paper](https://aclanthology.org/N16-1136/), and [Calc-X paper](https://arxiv.org/abs/2305.15017) as follows:
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```bibtex
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@inproceedings{kadlcik-etal-2023-soft,
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