Papers by Pavel Přibáň
Czech Dataset for Cross-lingual Subjectivity Classification (2022.lrec-1)
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| Challenge: | Using the existing English dataset, we can use the subjectivity classification to test the ability of pre-trained multilingual models to transfer knowledge between languages. |
| Approach: | They propose to use a Czech subjectivity dataset of 10k manually annotated subjective and objective sentences as a cross-lingual benchmark. |
| Outcome: | The proposed dataset is the first subjectivity dataset for the Czech language and also includes 200k automatically labeled sentences. |
Czech Dataset for Complex Aspect-Based Sentiment Analysis Tasks (2024.lrec-main)
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| Challenge: | 3.1K reviews are manually annotated for aspect-based sentiment analysis (ABSA) ABSA is a fine-grained task that aims to identify the sentiment associated with each aspect or characteristic of a text. |
| Approach: | They propose a new Czech dataset for aspect-based sentiment analysis . the new dataset is built upon the older Czech dataset . authors provide 24M reviews without annotations suitable for unsupervised learning . |
| Outcome: | The proposed dataset is built upon the older dataset, but is specifically designed for more complex tasks. |