Multilingual Extraction and Categorization of Lexical Collocations with Graph-aware Transformers
Luis Espinosa Anke, Alexander Shvets, Alireza Mohammadshahi, James Henderson, Leo Wanner
Abstract
Recognizing and categorizing lexical collocations in context is useful for language learning, dictionary compilation and downstream NLP. However, it is a challenging task due to the varying degrees of frozenness lexical collocations exhibit. In this paper, we put forward a sequence tagging BERT-based model enhanced with a graph-aware transformer architecture, which we evaluate on the task of collocation recognition in context. Our results suggest that explicitly encoding syntactic dependencies in the model architecture is helpful, and provide insights on differences in collocation typification in English, Spanish and French.- Anthology ID:
- 2022.starsem-1.8
- Volume:
- Proceedings of the 11th Joint Conference on Lexical and Computational Semantics
- Month:
- July
- Year:
- 2022
- Address:
- Seattle, Washington
- Editors:
- Vivi Nastase, Ellie Pavlick, Mohammad Taher Pilehvar, Jose Camacho-Collados, Alessandro Raganato
- Venue:
- *SEM
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 89–100
- Language:
- URL:
- https://aclanthology.org/2022.starsem-1.8
- DOI:
- 10.18653/v1/2022.starsem-1.8
- Cite (ACL):
- Luis Espinosa Anke, Alexander Shvets, Alireza Mohammadshahi, James Henderson, and Leo Wanner. 2022. Multilingual Extraction and Categorization of Lexical Collocations with Graph-aware Transformers. In Proceedings of the 11th Joint Conference on Lexical and Computational Semantics, pages 89–100, Seattle, Washington. Association for Computational Linguistics.
- Cite (Informal):
- Multilingual Extraction and Categorization of Lexical Collocations with Graph-aware Transformers (Espinosa Anke et al., *SEM 2022)
- PDF:
- https://preview.aclanthology.org/naacl-24-ws-corrections/2022.starsem-1.8.pdf
- Data
- Bio