Enriching Word Usage Graphs with Cluster Definitions
Andrey Kutuzov, Mariia Fedorova, Dominik Schlechtweg, Nikolay Arefyev
Abstract
We present a dataset of word usage graphs (WUGs), where the existing WUGs for multiple languages are enriched with cluster labels functioning as sense definitions. They are generated from scratch by fine-tuned encoder-decoder language models. The conducted human evaluation has shown that these definitions match the existing clusters in WUGs better than the definitions chosen from WordNet by two baseline systems. At the same time, the method is straightforward to use and easy to extend to new languages. The resulting enriched datasets can be extremely helpful for moving on to explainable semantic change modeling.- Anthology ID:
- 2024.lrec-main.546
- 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:
- 6189–6198
- Language:
- URL:
- https://aclanthology.org/2024.lrec-main.546
- DOI:
- Cite (ACL):
- Andrey Kutuzov, Mariia Fedorova, Dominik Schlechtweg, and Nikolay Arefyev. 2024. Enriching Word Usage Graphs with Cluster Definitions. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 6189–6198, Torino, Italia. ELRA and ICCL.
- Cite (Informal):
- Enriching Word Usage Graphs with Cluster Definitions (Kutuzov et al., LREC-COLING 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-2/2024.lrec-main.546.pdf