---
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

![Confusion matrix](cm.png)


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