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path: original-splits/test-*
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# Dataset Card for "Calc-asdiv_a"
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## Cite
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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:
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```bibtex
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@inproceedings{kadlcik-etal-2023-soft,
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- split: test
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path: original-splits/test-*
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---
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# Dataset Card for "Calc-asdiv_a"
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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 the arithmetic subset of ASDiv ([original repo](https://github.com/chaochun/nlu-asdiv-dataset)).
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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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- `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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- `result_unit`: the units of the result
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- `grade`: an estimate of the school grade in which the problem would be practiced
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- `source_question`: the source from which the example originates
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## Data splits
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The dataset does not contain data splits. We consider the whole dataset as a testing benchmark.
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## Licence
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CC BY-NC 4.0, consistent with the original source dataset linked above.
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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 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:
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```bibtex
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@inproceedings{kadlcik-etal-2023-soft,
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