| tags: | |
| - question-answering | |
| language: | |
| - ind | |
| # facqa | |
| 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 | |
| [https://github.com/IndoNLP/indonlu](https://github.com/IndoNLP/indonlu) | |
| ### NusaCatalogue | |
| For easy indexing and metadata: [https://indonlp.github.io/nusa-catalogue](https://indonlp.github.io/nusa-catalogue) |