ConSeC: Word Sense Disambiguation as Continuous Sense Comprehension

Edoardo Barba, Luigi Procopio, Roberto Navigli


Abstract
Supervised systems have nowadays become the standard recipe for Word Sense Disambiguation (WSD), with Transformer-based language models as their primary ingredient. However, while these systems have certainly attained unprecedented performances, virtually all of them operate under the constraining assumption that, given a context, each word can be disambiguated individually with no account of the other sense choices. To address this limitation and drop this assumption, we propose CONtinuous SEnse Comprehension (ConSeC), a novel approach to WSD: leveraging a recent re-framing of this task as a text extraction problem, we adapt it to our formulation and introduce a feedback loop strategy that allows the disambiguation of a target word to be conditioned not only on its context but also on the explicit senses assigned to nearby words. We evaluate ConSeC and examine how its components lead it to surpass all its competitors and set a new state of the art on English WSD. We also explore how ConSeC fares in the cross-lingual setting, focusing on 8 languages with various degrees of resource availability, and report significant improvements over prior systems. We release our code at https://github.com/SapienzaNLP/consec.
Anthology ID:
2021.emnlp-main.112
Volume:
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Month:
November
Year:
2021
Address:
Online and Punta Cana, Dominican Republic
Editors:
Marie-Francine Moens, Xuanjing Huang, Lucia Specia, Scott Wen-tau Yih
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1492–1503
Language:
URL:
https://aclanthology.org/2021.emnlp-main.112
DOI:
10.18653/v1/2021.emnlp-main.112
Bibkey:
Cite (ACL):
Edoardo Barba, Luigi Procopio, and Roberto Navigli. 2021. ConSeC: Word Sense Disambiguation as Continuous Sense Comprehension. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 1492–1503, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics.
Cite (Informal):
ConSeC: Word Sense Disambiguation as Continuous Sense Comprehension (Barba et al., EMNLP 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.emnlp-main.112.pdf
Video:
 https://aclanthology.org/2021.emnlp-main.112.mp4
Code
 sapienzanlp/consec
Data
Word Sense Disambiguation: a Unified Evaluation Framework and Empirical Comparison