metadata

license: cc-by-sa-4.0
task_categories:
  - text-classification
language:
  - cs
pretty_name: Czech SNLI

Dataset Card for Czech SNLI

Czech translation of the [https://nlp.stanford.edu/projects/snli/](Stanford Natural Language Interface) (SNLI) dataset with manual annotation of a SNLI subset. In addition to the entailment/contradiction/neutral inference, a "bad translation" class was added.

The annotation was done by students of NLP or computational linguistics. 1499 same pairs were annotated by two students to check IAA.

Dataset Details

The annotation for Czech premise-hypothesis pairs is done on 165390 pairs from train, test, and dev parts of the SNLI in the following distribution:

train: 159650
dev: 2860
test: 2880

The premise-hypothesis pairs were translated using the LINDAT Translation at https://lindat.mff.cuni.cz/services/translation/. The CUBBITT model was published as:

Popel, M., Tomkova, M., Tomek, J. et al. Transforming machine translation: a deep learning system reaches news translation quality comparable to human professionals. Nat Commun 11, 4381 (2020). https://doi.org/10.1038/s41467-020-18073-9

Inter-Annotator Agreement

Two random annotators obtained the same dataset. The kappa score is 0.67 (substantial agreement).

Confusion matrix

Full report on the agreement

Simple Kappa Coefficient
          --------------------------------
          Kappa                     0.6757
          ASE                       0.0146
          95% Lower Conf Limit      0.6470
          95% Upper Conf Limit      0.7044

             Test of H0: Simple Kappa = 0

          ASE under H0              0.0154
          Z                         43.9031
          One-sided Pr >  Z         0.0000
          Two-sided Pr > |Z|        0.0000