language:ind question-answering arxiv:2210.13778 region:us
I(n)dontKnow-MRC (IDK-MRC) is an Indonesian Machine Reading Comprehension dataset that covers
answerable and unanswerable questions. Based on the combination of the existing answerable questions in TyDiQA,
the new unanswerable question in IDK-MRC is generated using a question generation model and human-written question.
Each paragraph in the dataset has a set of answerable and unanswerable questions with the corresponding answer.

Besides IDK-MRC (idk_mrc) dataset, several baseline datasets also provided:
1. Trans SQuAD (trans_squad): machine translated SQuAD 2.0 (Muis and Purwarianti, 2020)
2. TyDiQA (tydiqa): Indonesian answerable questions set from the TyDiQA-GoldP (Clark et al., 2020)
3. Model Gen (model_gen): TyDiQA + the unanswerable questions output from the question generation model
4. Human Filt (human_filt): Model Gen dataset that has been filtered by human annotator
@misc{putri2022idk,
    doi = {10.48550/ARXIV.2210.13778},
    url = {https://arxiv.org/abs/2210.13778},
    author = {Putri, Rifki Afina and Oh, Alice},
    title = {IDK-MRC: Unanswerable Questions for Indonesian Machine Reading Comprehension},
    publisher = {arXiv},
    year = {2022}
}
---
tags:
- question-answering
language:
- ind
---

# idk_mrc

I(n)dontKnow-MRC (IDK-MRC) is an Indonesian Machine Reading Comprehension dataset that covers

answerable and unanswerable questions. Based on the combination of the existing answerable questions in TyDiQA,

the new unanswerable question in IDK-MRC is generated using a question generation model and human-written question.

Each paragraph in the dataset has a set of answerable and unanswerable questions with the corresponding answer.



Besides IDK-MRC (idk_mrc) dataset, several baseline datasets also provided:

1. Trans SQuAD (trans_squad): machine translated SQuAD 2.0 (Muis and Purwarianti, 2020)

2. TyDiQA (tydiqa): Indonesian answerable questions set from the TyDiQA-GoldP (Clark et al., 2020)

3. Model Gen (model_gen): TyDiQA + the unanswerable questions output from the question generation model

4. Human Filt (human_filt): Model Gen dataset that has been filtered by human annotator

## Dataset Usage

Run `pip install nusacrowd` before loading the dataset through HuggingFace's `load_dataset`.

## Citation

```
@misc{putri2022idk,
    doi = {10.48550/ARXIV.2210.13778},
    url = {https://arxiv.org/abs/2210.13778},
    author = {Putri, Rifki Afina and Oh, Alice},
    title = {IDK-MRC: Unanswerable Questions for Indonesian Machine Reading Comprehension},
    publisher = {arXiv},
    year = {2022}
}
```

## License

CC-BY-SA 4.0

## Homepage

[https://github.com/rifkiaputri/IDK-MRC](https://github.com/rifkiaputri/IDK-MRC)

### NusaCatalogue

For easy indexing and metadata: [https://indonlp.github.io/nusa-catalogue](https://indonlp.github.io/nusa-catalogue)