Dataset:



Dataset Card for "kor_nli"

Dataset Summary

Korean Natural Language Inference datasets

Supported Tasks

More Information Needed

Languages

More Information Needed

Dataset Structure

We show detailed information for up to 5 configurations of the dataset.

Data Instances

multi_nli

  • Size of downloaded dataset files: 40.16 MB
  • Size of the generated dataset: 80.80 MB
  • Total amount of disk used: 120.97 MB

An example of 'train' looks as follows.

snli

  • Size of downloaded dataset files: 40.16 MB
  • Size of the generated dataset: 76.42 MB
  • Total amount of disk used: 116.59 MB

An example of 'train' looks as follows.

xnli

  • Size of downloaded dataset files: 40.16 MB
  • Size of the generated dataset: 1.49 MB
  • Total amount of disk used: 41.66 MB

An example of 'validation' looks as follows.

Data Fields

The data fields are the same among all splits.

multi_nli

  • premise: a string feature.
  • hypothesis: a string feature.
  • label: a classification label, with possible values including entailment (0), neutral (1), contradiction (2).

snli

  • premise: a string feature.
  • hypothesis: a string feature.
  • label: a classification label, with possible values including entailment (0), neutral (1), contradiction (2).

xnli

  • premise: a string feature.
  • hypothesis: a string feature.
  • label: a classification label, with possible values including entailment (0), neutral (1), contradiction (2).

Data Splits Sample Size

multi_nli

train
multi_nli 392702

snli

train
snli 550152

xnli

validation test
xnli 2490 5010

Dataset Creation

Curation Rationale

More Information Needed

Source Data

More Information Needed

Annotations

More Information Needed

Personal and Sensitive Information

More Information Needed

Considerations for Using the Data

Social Impact of Dataset

More Information Needed

Discussion of Biases

More Information Needed

Other Known Limitations

More Information Needed

Additional Information

Dataset Curators

More Information Needed

Licensing Information

More Information Needed

Citation Information

@article{ham2020kornli,
  title={KorNLI and KorSTS: New Benchmark Datasets for Korean Natural Language Understanding},
  author={Ham, Jiyeon and Choe, Yo Joong and Park, Kyubyong and Choi, Ilji and Soh, Hyungjoon},
  journal={arXiv preprint arXiv:2004.03289},
  year={2020}
}

Contributions

Thanks to @thomwolf, @lhoestq, @lewtun, @patrickvonplaten for adding this dataset.

Update on GitHub
Explore dataset Edit Model Tags

Models trained or fine-tuned on kor_nli

None yet