AMuSE-WSD: An All-in-one Multilingual System for Easy Word Sense Disambiguation

Riccardo Orlando, Simone Conia, Fabrizio Brignone, Francesco Cecconi, Roberto Navigli


Abstract
Over the past few years, Word Sense Disambiguation (WSD) has received renewed interest: recently proposed systems have shown the remarkable effectiveness of deep learning techniques in this task, especially when aided by modern pretrained language models. Unfortunately, such systems are still not available as ready-to-use end-to-end packages, making it difficult for researchers to take advantage of their performance. The only alternative for a user interested in applying WSD to downstream tasks is to rely on currently available end-to-end WSD systems, which, however, still rely on graph-based heuristics or non-neural machine learning algorithms. In this paper, we fill this gap and propose AMuSE-WSD, the first end-to-end system to offer high-quality sense information in 40 languages through a state-of-the-art neural model for WSD. We hope that AMuSE-WSD will provide a stepping stone for the integration of meaning into real-world applications and encourage further studies in lexical semantics. AMuSE-WSD is available online at http://nlp.uniroma1.it/amuse-wsd.
Anthology ID:
2021.emnlp-demo.34
Volume:
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
Month:
November
Year:
2021
Address:
Online and Punta Cana, Dominican Republic
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
298–307
Language:
URL:
https://aclanthology.org/2021.emnlp-demo.34
DOI:
10.18653/v1/2021.emnlp-demo.34
Bibkey:
Cite (ACL):
Riccardo Orlando, Simone Conia, Fabrizio Brignone, Francesco Cecconi, and Roberto Navigli. 2021. AMuSE-WSD: An All-in-one Multilingual System for Easy Word Sense Disambiguation. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pages 298–307, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics.
Cite (Informal):
AMuSE-WSD: An All-in-one Multilingual System for Easy Word Sense Disambiguation (Orlando et al., EMNLP 2021)
Copy Citation:
PDF:
https://preview.aclanthology.org/ingestion-script-update/2021.emnlp-demo.34.pdf
Video:
 https://preview.aclanthology.org/ingestion-script-update/2021.emnlp-demo.34.mp4
Data
Word Sense Disambiguation: a Unified Evaluation Framework and Empirical Comparison