Dataset Card for Calc-ape210k

Summary

This dataset is an instance of Ape210K 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 to 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 outsource the computations in the reasoning chain to a calculator.

Construction Process

First, we translated the questions into English using Google Translate. Next, we parsed the equations and the results. We linearized the equations into a sequence of elementary steps and evaluated them using a sympy-based calculator. We numerically compare the output with the result in the data and remove all examples where they do not match (less than 3% loss in each split). Finally, we save the chain of steps in the HTML-like language in the chain column. We keep the original columns in the dataset for convenience. We also perform in-dataset and cross-dataset data-leak detection within Calc-X collection. Specifically for Ape210k, we removed parts of the validation and test split, with around 1700 remaining in each.

You can read more information about this process in our Calc-X paper.

Data splits

The default config contains filtered splits with data leaks removed. You can load it using:

datasets.load_dataset("MU-NLPC/calc-ape210k")

In the original-splits config, the data splits are unfiltered and correspond to the original Ape210K dataset. See ape210k dataset github and the paper for more info. You can load it using:

datasets.load_dataset("MU-NLPC/calc-ape210k", "original-splits")

Attributes

• id - id of the example
• question - the description of the math problem. Automatically translated from the question_chinese column into English using Google Translate
• question_chinese - the original description of the math problem in Chinese
• chain - linearized equation, sequence of arithmetic steps in HTML-like language that can be evaluated using our sympy-based calculator
• result - result as a string (can be an integer, float, or a fraction)
• result_float - result, converted to a float
• equation - a nested expression that evaluates to the correct answer

Attributes id, question, chain, and result are present in all datasets in 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:

• original Ape210k dataset and repo
• original Ape210k paper

Licence

MIT, consistently with the original dataset.

Cite

If you use this version of the dataset in research, please cite the original Ape210k paper, and the Calc-X paper 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",
}