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--- |
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license: cc-by-sa-4.0 |
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task_categories: |
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- text-classification |
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language: |
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- cs |
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pretty_name: Czech SNLI |
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--- |
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# Dataset Card for Czech SNLI |
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Czech translation of the [https://nlp.stanford.edu/projects/snli/](Stanford Natural Language Interface) (SNLI) dataset with manual annotation of a SNLI subset. |
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In addition to the entailment/contradiction/neutral inference, a "bad translation" class was added. |
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The annotation was done by students of NLP or computational linguistics. 1499 same pairs were annotated by two students to check IAA. |
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## Dataset Details |
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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: |
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- train: 159650 |
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- dev: 2860 |
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- test: 2880 |
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The premise-hypothesis pairs were translated using the LINDAT Translation at https://lindat.mff.cuni.cz/services/translation/. |
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The CUBBITT model was published as: |
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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 |
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## Inter-Annotator Agreement |
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Two random annotators obtained the same dataset. The kappa score is 0.67 (substantial agreement). |
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Confusion matrix |
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Full report on the agreement |
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Simple Kappa Coefficient |
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-------------------------------- |
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Kappa 0.6757 |
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ASE 0.0146 |
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95% Lower Conf Limit 0.6470 |
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95% Upper Conf Limit 0.7044 |
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Test of H0: Simple Kappa = 0 |
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ASE under H0 0.0154 |
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Z 43.9031 |
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One-sided Pr > Z 0.0000 |
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Two-sided Pr > |Z| 0.0000 |
