CZLC/cs_naturalquestions

---
language:
- cs
license: cc-by-sa-3.0
---
This dataset is automatic translation of [Natural Questions Open](https://huggingface.co/datasets/google-research-datasets/nq_open) dataset into Czech (Kwiatkovski et al., 2019; Lee et al., 2021).
The dataset was translated using [LINDAT Translation Service](https://lindat.mff.cuni.cz/services/translation/docs) available as an online-API.

## Licensing Information
The [original dataset](https://huggingface.co/datasets/google-research-datasets/nq_open) is licensed under [CC-BY-SA-3.0](https://creativecommons.org/licenses/by-sa/3.0/deed.en).
Members of CZLC do not own the copyright of the questions and answers included in NaturalQuestions. We are not responsible for their content or meaning. The dataset is intended for non-commercial research purposes only.

## Citing the original work
```bibtex
@article{kwiatkowski2019natural,
title={Natural questions: a benchmark for question answering research},
author={Kwiatkowski, Tom and Palomaki, Jennimaria and Redfield, Olivia and Collins, Michael and Parikh, Ankur and Alberti, Chris and Epstein, Danielle and Polosukhin, Illia and Devlin, Jacob and Lee, Kenton and others},
journal={Transactions of the Association for Computational Linguistics},
volume={7},
pages={453--466},
year={2019},
publisher={MIT Press One Rogers Street, Cambridge, MA 02142-1209, USA journals-info~…}
}
@inproceedings{lee2019latent,
title={Latent Retrieval for Weakly Supervised Open Domain Question Answering},
author={Lee, Kenton and Chang, Ming-Wei and Toutanova, Kristina},
booktitle={Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics},
pages={6086--6096},
year={2019}
}
```

## Contact
Correspondence to: `[e-mail]`.