Abstract
State-of-the-art methods for Word Sense Disambiguation (WSD) combine two different features: the power of pre-trained language models and a propagation method to extend the coverage of such models. This propagation is needed as current sense-annotated corpora lack coverage of many instances in the underlying sense inventory (usually WordNet). At the same time, unambiguous words make for a large portion of all words in WordNet, while being poorly covered in existing sense-annotated corpora. In this paper, we propose a simple method to provide annotations for most unambiguous words in a large corpus. We introduce the UWA (Unambiguous Word Annotations) dataset and show how a state-of-the-art propagation-based model can use it to extend the coverage and quality of its word sense embeddings by a significant margin, improving on its original results on WSD.- Anthology ID:
- 2020.emnlp-main.283
- Volume:
- Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
- Month:
- November
- Year:
- 2020
- Address:
- Online
- Venue:
- EMNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 3514–3520
- Language:
- URL:
- https://aclanthology.org/2020.emnlp-main.283
- DOI:
- 10.18653/v1/2020.emnlp-main.283
- Cite (ACL):
- Daniel Loureiro and Jose Camacho-Collados. 2020. Don’t Neglect the Obvious: On the Role of Unambiguous Words in Word Sense Disambiguation. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 3514–3520, Online. Association for Computational Linguistics.
- Cite (Informal):
- Don’t Neglect the Obvious: On the Role of Unambiguous Words in Word Sense Disambiguation (Loureiro & Camacho-Collados, EMNLP 2020)
- PDF:
- https://preview.aclanthology.org/auto-file-uploads/2020.emnlp-main.283.pdf