Datasets:

Languages:
English
Multilinguality:
monolingual
Size Categories:
10K<n<100K
Annotations Creators:
crowdsourced
Source Datasets:
extended|aqua_rat
Tags:
License:
albertvillanova HF staff commited on
Commit
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1 Parent(s): c8d38ca

Fix documentation card of math_qa dataset (#4884)

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Commit from https://github.com/huggingface/datasets/commit/6c327f19c07c092c86580e9f5e671a14c523be3e

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  1. README.md +43 -6
README.md CHANGED
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  ---
 
 
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  language:
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  - en
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- paperswithcode_id: mathqa
 
 
 
 
 
 
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  pretty_name: MathQA
 
 
 
 
 
 
 
 
 
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  ---
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- # Dataset Card for "math_qa"
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  ## Table of Contents
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  - [Dataset Description](#dataset-description)
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  - **Homepage:** [https://math-qa.github.io/math-QA/](https://math-qa.github.io/math-QA/)
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  - **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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- - **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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  - **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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  - **Size of downloaded dataset files:** 6.96 MB
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  - **Size of the generated dataset:** 21.90 MB
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  ### Dataset Summary
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- Our dataset is gathered by using a new representation language to annotate over the AQuA-RAT dataset. AQuA-RAT has provided the questions, options, rationale, and the correct options.
 
 
 
 
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  ### Supported Tasks and Leaderboards
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  ### Licensing Information
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- [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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  ### Citation Information
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  ```
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-
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ```
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  ---
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+ annotations_creators:
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+ - crowdsourced
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  language:
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  - en
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+ language_creators:
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+ - crowdsourced
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+ - expert-generated
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+ license:
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+ - apache-2.0
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+ multilinguality:
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+ - monolingual
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  pretty_name: MathQA
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+ size_categories:
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+ - 10K<n<100K
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+ source_datasets:
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+ - extended|aqua_rat
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+ task_categories:
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+ - question-answering
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+ task_ids:
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+ - multiple-choice-qa
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+ paperswithcode_id: mathqa
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  ---
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+ # Dataset Card for MathQA
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  ## Table of Contents
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  - [Dataset Description](#dataset-description)
 
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  - **Homepage:** [https://math-qa.github.io/math-QA/](https://math-qa.github.io/math-QA/)
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  - **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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+ - **Paper:** [MathQA: Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms](https://aclanthology.org/N19-1245/)
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  - **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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  - **Size of downloaded dataset files:** 6.96 MB
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  - **Size of the generated dataset:** 21.90 MB
 
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  ### Dataset Summary
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+ We introduce a large-scale dataset of math word problems.
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+
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+ Our dataset is gathered by using a new representation language to annotate over the AQuA-RAT dataset with fully-specified operational programs.
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+
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+ AQuA-RAT has provided the questions, options, rationale, and the correct options.
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  ### Supported Tasks and Leaderboards
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  ### Licensing Information
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+ The dataset is licensed under the [Apache License, Version 2.0](http://www.apache.org/licenses/LICENSE-2.0).
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  ### Citation Information
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  ```
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+ @inproceedings{amini-etal-2019-mathqa,
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+ title = "{M}ath{QA}: Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms",
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+ author = "Amini, Aida and
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+ Gabriel, Saadia and
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+ Lin, Shanchuan and
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+ Koncel-Kedziorski, Rik and
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+ Choi, Yejin and
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+ Hajishirzi, Hannaneh",
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+ booktitle = "Proceedings of the 2019 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)",
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+ month = jun,
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+ year = "2019",
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+ address = "Minneapolis, Minnesota",
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+ publisher = "Association for Computational Linguistics",
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+ url = "https://aclanthology.org/N19-1245",
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+ doi = "10.18653/v1/N19-1245",
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+ pages = "2357--2367",
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+ }
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  ```
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