Papers › Czech Dataset for Cross-lingual Subjectivity Classification
Czech Dataset for Cross-lingual Subjectivity Classification
Pavel Přibáň, Josef Steinberger
In this paper, we introduce a new Czech subjectivity dataset of 10k manually annotated subjective and objective sentences from movie reviews and descriptions. Our prime motivation is to provide a reliable dataset that can be used with the existing English dataset as a benchmark to test the ability of pre-trained multilingual models to transfer knowledge between Czech and English and vice versa. Two annotators annotated the dataset reaching 0.83 of the Cohen's \k{appa} inter-annotator agreement. To the best of our knowledge, this is the first subjectivity dataset for the Czech language. We also created an additional dataset that consists of 200k automatically labeled sentences. Both datasets are freely available for research purposes. Furthermore, we fine-tune five pre-trained BERT-like models to set a monolingual baseline for the new dataset and we achieve 93.56% of accuracy. We fine-tune models on the existing English dataset for which we obtained results that are on par with the current state-of-the-art results. Finally, we perform zero-shot cross-lingual subjectivity classification between Czech and English to verify the usability of our dataset as the cross-lingual benchmark. We compare and discuss the cross-lingual and monolingual results and the ability of multilingual models to transfer knowledge between languages.
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Datasets
Introduced by this paper, per the archive.
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Subjectivity Analysis | Czech Subjectivity Dataset | XLM-R-Large | Accuracy | 93.56 | #1 of 5 | Archive leaderboard | report |
| Subjectivity Analysis | Czech Subjectivity Dataset | RobeCzech | Accuracy | 93.29 | #2 of 5 | Archive leaderboard | report |
| Subjectivity Analysis | Czech Subjectivity Dataset | Czert-B | Accuracy | 92.85 | #3 of 5 | Archive leaderboard | report |
| Subjectivity Analysis | Czech Subjectivity Dataset | Czech Electra | Accuracy | 91.85 | #4 of 5 | Archive leaderboard | report |
| Subjectivity Analysis | Czech Subjectivity Dataset | mBERT | Accuracy | 91.23 | #5 of 5 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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