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