metadata
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