Abstract
A useful semantic role-annotated resource for training semantic role models for the German language is missing. We point out some problems of previous resources and provide a new one due to a combined translation and alignment process: The gold standard CoNLL-2012 semantic role annotations are translated into German. Semantic role labels are transferred due to alignment models. The resulting dataset is used to train a German semantic role model. With F1-scores around 0.7, the major roles achieve competitive evaluation scores, but avoid limitations of previous approaches. The described procedure can be applied to other languages as well.- Anthology ID:
- 2024.lrec-main.682
- Volume:
- Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
- Month:
- May
- Year:
- 2024
- Address:
- Torino, Italia
- Editors:
- Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, Nianwen Xue
- Venues:
- LREC | COLING
- SIG:
- Publisher:
- ELRA and ICCL
- Note:
- Pages:
- 7717–7727
- Language:
- URL:
- https://aclanthology.org/2024.lrec-main.682
- DOI:
- Cite (ACL):
- Maxim Konca, Andy Luecking, and Alexander Mehler. 2024. German SRL: Corpus Construction and Model Training. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 7717–7727, Torino, Italia. ELRA and ICCL.
- Cite (Informal):
- German SRL: Corpus Construction and Model Training (Konca et al., LREC-COLING 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2024.lrec-main.682.pdf