Abstract
This paper focuses on the task of word sense disambiguation (WSD) on lexicographic examples relying on the French Lexical Network (fr-LN). For this purpose, we exploit the lexical and relational properties of the network, that we integrated in a feedforward neural WSD model on top of pretrained French BERT embeddings. We provide a comparative study with various models and further show the impact of our approach regarding polysemic units.- Anthology ID:
- 2022.textgraphs-1.8
- Volume:
- Proceedings of TextGraphs-16: Graph-based Methods for Natural Language Processing
- Month:
- October
- Year:
- 2022
- Address:
- Gyeongju, Republic of Korea
- Editors:
- Dmitry Ustalov, Yanjun Gao, Alexander Panchenko, Marco Valentino, Mokanarangan Thayaparan, Thien Huu Nguyen, Gerald Penn, Arti Ramesh, Abhik Jana
- Venue:
- TextGraphs
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 70–76
- Language:
- URL:
- https://aclanthology.org/2022.textgraphs-1.8
- DOI:
- Cite (ACL):
- Aman Sinha, Sandrine Ollinger, and Mathieu Constant. 2022. Word Sense Disambiguation of French Lexicographical Examples Using Lexical Networks. In Proceedings of TextGraphs-16: Graph-based Methods for Natural Language Processing, pages 70–76, Gyeongju, Republic of Korea. Association for Computational Linguistics.
- Cite (Informal):
- Word Sense Disambiguation of French Lexicographical Examples Using Lexical Networks (Sinha et al., TextGraphs 2022)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-1/2022.textgraphs-1.8.pdf
- Code
- atilf-umr7118/graphwsd