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---
tags:
- question-answering
language:
- ind
---
FacQA: The goal of the FacQA dataset is to find the answer to a question from a provided short passage from a news article.
Each row in the FacQA dataset consists of a question, a short passage, and a label phrase, which can be found inside the
corresponding short passage. There are six categories of questions: date, location, name,
organization, person, and quantitative.
## Dataset Usage
Run `pip install nusacrowd` before loading the dataset through HuggingFace's `load_dataset`.
## Citation
```
@inproceedings{purwarianti2007machine,
title={A Machine Learning Approach for Indonesian Question Answering System},
author={Ayu Purwarianti, Masatoshi Tsuchiya, and Seiichi Nakagawa},
booktitle={Proceedings of Artificial Intelligence and Applications },
pages={573--578},
year={2007}
}
```
## License
CC-BY-SA 4.0
## Homepage
### NusaCatalogue
For easy indexing and metadata: [https://indonlp.github.io/nusa-catalogue](https://indonlp.github.io/nusa-catalogue) |