Özlem Karabulut

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2025

pdf bib
Tuebingen at SemEval-2025 Task 10: Class Weighting, External Knowledge and Data Augmentation in BERT Models
Özlem Karabulut | Soudabeh Eslami | Ali Gharaee | Matthew Andrews
Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)

The spread of disinformation and propaganda in online news presents a significant challengeto information integrity. As part of the SemEval 2025 Task-10 on Multilingual Characterization and Extraction of Narratives from Online News, this study focuses on Subtask 1: Entity Framing, which involves assigning roles to named entities within news articles across multiple languages.We investigate techniques such as data augmentation, external knowledge, and class weighting to improve classification performance. Our findings indicate that class weighting was more effective than other approaches
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