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# MASH-QA Dataset
MASH-QA is a dataset tailored for Question Answering (QA) tasks in the consumer health domain. It is designed to facilitate information extraction from long and comprehensive documents, focusing on answering generally non-factoid questions. Unlike traditional Machine Reading Comprehension (MRC) datasets that feature short, single-span answers, MASH-QA provides answers that are often multi-sentential and sourced from multiple spans of long context articles.
## Features of MASH-QA
- **Domain**: Consumer Health
- **Context Length**: Long healthcare articles
- **Question Type**: Generally non-factoid
- **Answer Type**: Multi-span, multi-sentence, and excerpted from various parts of the context.
## Dataset Details
MASH-QA enables researchers to:
- Explore multi-span extraction techniques for long contexts.
- Develop models capable of handling complex QA tasks with long, non-contiguous answers.
## Citation
If you use the MASH-QA dataset in your research, please cite the following paper:
@inproceedings{zhu2020question, title={Question Answering with Long Multiple-Span Answers}, author={Ming Zhu and Aman Ahuja and Da-Cheng Juan and Wei Wei and Chandan K. Reddy}, booktitle={Findings of the Association for Computational Linguistics: EMNLP 2020}, pages={3840--3849}, year={2020}, organization={Association for Computational Linguistics} }
## Paper
Ming Zhu, Aman Ahuja, Da-Cheng Juan, Wei Wei, and Chandan K. Reddy. 2020. [Question Answering with Long Multiple-Span Answers](https://doi.org/10.18653/v1/2020.findings-emnlp.342). In *Findings of the Association for Computational Linguistics: EMNLP 2020*. Association for Computational Linguistics, Online, 3840–3849.
## Dataset Access
The dataset is publicly available on GitHub. To access the dataset, visit the following link:
- **GitHub Repository**: [MASH-QA](https://github.com/mingzhu0527/MASHQA)
## Usage
The MASH-QA dataset is ideal for tasks such as:
- Long-form Question Answering
- Multi-span Extraction
- Healthcare Informatics Research
## License
Please refer to the GitHub repository for license details.
## Contact
For any questions or inquiries related to the dataset, please visit the [GitHub Issues](https://github.com/mingzhu0527/MASHQA/issues) page in the repository.
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