metadata

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

NusaCatalogue

For easy indexing and metadata: https://indonlp.github.io/nusa-catalogue