metadata

license: mit
dataset_info:
  config_name: original-splits
  features:
    - name: id
      dtype: string
    - name: question
      dtype: string
    - name: question_chinese
      dtype: string
    - name: chain
      dtype: string
    - name: result
      dtype: string
    - name: result_float
      dtype: float64
    - name: equation
      dtype: string
  splits:
    - name: train
      num_bytes: 111988047
      num_examples: 195179
    - name: validation
      num_bytes: 2798479
      num_examples: 4867
    - name: test
      num_bytes: 2793355
      num_examples: 4867
  download_size: 52234086
  dataset_size: 117579881
configs:
  - config_name: original-splits
    data_files:
      - split: train
        path: original-splits/train-*
      - split: validation
        path: original-splits/validation-*
      - split: test
        path: original-splits/test-*

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 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 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 the HTML-like language in the chain column. We keep the original columns in the dataset for convenience.

You can read more information about this process in our technical report.

Content and Data splits

Content and splits correspond to the original Ape210K dataset. See ape210k dataset github and the paper for more info.

Columns:

id - id of the example
question - the description of the math problem. Automatically translated from question_chinese column into English using Google Translate
question_chinese - 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 integer, float or a fraction)
result_float - result as a float
equation - a nested expression that evaluates to the correct answer

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 also our technical report as follows:

@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}
}