Datasets:

Languages:
Indonesian
ArXiv:
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  - question-answering
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  language:
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  - ind
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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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+ I(n)dontKnow-MRC (IDK-MRC) is an Indonesian Machine Reading Comprehension dataset that covers
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+ answerable and unanswerable questions. Based on the combination of the existing answerable questions in TyDiQA,
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+ the new unanswerable question in IDK-MRC is generated using a question generation model and human-written question.
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+ Each paragraph in the dataset has a set of answerable and unanswerable questions with the corresponding answer.
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+
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+ Besides IDK-MRC (idk_mrc) dataset, several baseline datasets also provided:
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+ 1. Trans SQuAD (trans_squad): machine translated SQuAD 2.0 (Muis and Purwarianti, 2020)
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+ 2. TyDiQA (tydiqa): Indonesian answerable questions set from the TyDiQA-GoldP (Clark et al., 2020)
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+ 3. Model Gen (model_gen): TyDiQA + the unanswerable questions output from the question generation model
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+ 4. Human Filt (human_filt): Model Gen dataset that has been filtered by human annotator
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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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+ ```@misc{putri2022idk,
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+ doi = {10.48550/ARXIV.2210.13778},
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+ url = {https://arxiv.org/abs/2210.13778},
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+ author = {Putri, Rifki Afina and Oh, Alice},
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+ title = {IDK-MRC: Unanswerable Questions for Indonesian Machine Reading Comprehension},
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+ publisher = {arXiv},
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+ year = {2022}
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+ }
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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)