Datasets:
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---
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 |