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--- |
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language: |
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- en |
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license: apache-2.0 |
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size_categories: |
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- 10K<n<100K |
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task_categories: |
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- question-answering |
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pretty_name: AQUA-RAT with Calculator |
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dataset_info: |
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config_name: original-splits |
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features: |
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- name: id |
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dtype: string |
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- name: question |
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dtype: string |
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- name: chain |
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dtype: string |
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- name: result |
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dtype: string |
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- name: options |
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struct: |
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- name: A |
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dtype: string |
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- name: B |
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dtype: string |
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- name: C |
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dtype: string |
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- name: D |
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dtype: string |
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- name: E |
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dtype: string |
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- name: question_without_options |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 74265737 |
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num_examples: 97467 |
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- name: validation |
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num_bytes: 212928 |
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num_examples: 254 |
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- name: test |
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num_bytes: 206180 |
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num_examples: 254 |
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download_size: 42873590 |
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dataset_size: 74684845 |
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configs: |
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- config_name: original-splits |
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data_files: |
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- split: train |
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path: original-splits/train-* |
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- split: validation |
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path: original-splits/validation-* |
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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-aqua_rat" |
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### Summary |
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This dataset is an instance of [aqua_rat](https://huggingface.co/datasets/aqua_rat) dataset extended for the in-context calls of calculator, |
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represented by the `exec` calls to a `sympy` library. |
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### Supported Tasks |
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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 out-source the computations in the reasoning chain to a calculator. |
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### Construction Process |
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The dataset was constructed automatically by evaluating all candidate calls to a `sympy` library that were extracted from the originally-annotated |
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*rationale*s. The selection of candidates is pivoted by the matching of equals ('=') symbols in the chain, where the left-hand side of the equation is evaluated, |
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and accepted as a correct gadget call, if the result occurs closely on the right-hand side. |
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Therefore, the extraction of calculator calls may inhibit false negatives (where the calculator could have been used but was not), but not any known |
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false positives. |
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A full description of the extraction process can be found in the [corresponding parse script](https://github.com/markcheeky/gadgets/blob/7799a7841940b15593d4667219424ee71c74327e/gadgets/aqua.py#L19), |
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**If you find an issue in the dataset or in the fresh version of the parsing script, we'd be happy if you report it, or create a PR.** |
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## Dataset Structure |
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The dataset can be loaded by simply choosing a split (`train`, `validation` or `test`) and calling: |
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```python |
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import datasets |
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dataset_val = datasets.load_dataset("MU-NLPC/Calc-aqua_rat", split="validation") |
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print(dataset_val[0]) # see the output below |
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``` |
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### Data Instances |
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The samples of Calc-aqua_rat have this format (newline-reformated for better readability): |
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```python |
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{'question': 'Three birds are flying at a fast rate of 900 kilometers per hour. What is their speed in miles per minute? [1km = 0.6 miles]', |
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'options': {'A': '32400', 'B': '6000', 'C': '600', 'D': '60000', 'E': '10'}, |
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'result': 'A', |
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'chain': 'To calculate the equivalent of miles in a kilometer\n |
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0.6 kilometers \n= 1 mile\n |
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900 kilometers \n= (0.6)*900\n= \n<gadget id="calculator">(0.6)*900</gadget>\n<output>540</output>\n540 miles\n |
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In 1 hour there are 60 minutes\n |
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Speed in miles/minutes\n= 60 * 540\n= \n<gadget id="calculator">60 * 540</gadget>\n<output>32_400</output>\n32400\n |
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Correct answer - 32400\n. |
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<result>A</result>' |
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} |
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``` |
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The enclosing HTML tags (e.g. **`<gadget id="calculator">(0.6)*900</gadget>\n<output>540</output>`**) represent the inputs and outputs |
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to the `sympy.parse_expr().evalf()` method (in our code [here](https://github.com/markcheeky/gadgets/blob/7799a7841940b15593d4667219424ee71c74327e/gadgets/gadget.py#L28)). |
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Note that the format of the dataset is consistent with [MU-NLPC/Calc-gsm8k](https://huggingface.co/datasets/MU-NLPC/Calc-gsm8k). |
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### Data Fields |
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* **question**: A natural language definition of the problem to solve. |
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* **options**: 5 possible options (A, B, C, D and E), among which one is correct |
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* **result**: The correct option |
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* **chain**: A natural language step-by-step solution with automatically inserted calculator calls and outputs of the sympy calculator. |
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### Data Splits |
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The samples in data splits are consistent with the original [aqua_rat](https://huggingface.co/datasets/aqua_rat) dataset, containing: |
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* **train** split of 97467 samples, |
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* **validation** split of 254 samples, |
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* **test** split of 254. |
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* |
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## Licensing |
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Apache-2.0, consistently with the original aqua-rat dataset. |
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## Cite |
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If you use this dataset in research, please cite the original [aqua-rat paper](https://arxiv.org/pdf/1705.04146.pdf) and our report as follows: |
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```bibtex |
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@article{kadlcik2023calcx, |
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title={Calc-X: Enriching Arithmetical Chain-of-Thoughts Datasets by Interaction with Symbolic Systems}, |
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author={Marek Kadlčík and Michal Štefánik}, |
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year={2023}, |
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eprint={2305.15017}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.LG} |
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} |
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``` |