A Game-Theoretic Approach to Word Sense Disambiguation [PDF]
Computational Linguistics, 2016 This article presents a new model for word sense disambiguation formulated in terms of evolutionary game theory, where each word to be disambiguated is represented as a node on a graph whose edges represent word relations and senses are represented as ...
Rocco Tripodi, Marcello Pelillo
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The Interaction of Knowledge Sources in Word Sense Disambiguation [PDF]
Computational Linguistics, 2021 Mark Stevenson, Yorick Wilks
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Structural semantic interconnections: a knowledge-based approach to word sense disambiguation [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005 Roberto Navigli, Paola Velardi
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Moving Down the Long Tail of Word Sense Disambiguation with Gloss Informed Bi-encoders [PDF]
Annual Meeting of the Association for Computational Linguistics, 2020 A major obstacle in Word Sense Disambiguation (WSD) is that word senses are not uniformly distributed, causing existing models to generally perform poorly on senses that are either rare or unseen during training.
Terra Blevins, Luke Zettlemoyer
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Multilingual Word Sense Disambiguation with Unified Sense Representation [PDF]
International Conference on Computational Linguistics, 2022 As a key natural language processing (NLP) task, word sense disambiguation (WSD) evaluates how well NLP models can understand the fine-grained semantics of words under specific contexts. Benefited from the large-scale annotation, current WSD systems have
Ying Su +3 more
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SemEval-2023 Task 1: Visual Word Sense Disambiguation
International Workshop on Semantic Evaluation, 2023 This paper presents the Visual Word Sense Disambiguation (Visual-WSD) task.The objective of Visual-WSD is to identify among a set of ten images the one that corresponds to the intended meaning of a given ambiguous word which is accompanied with minimal ...
Alessandro Raganato +4 more
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Word Sense Disambiguation Using Clustered Sense Labels
Applied Sciences, 2022 Sequence labeling models for word sense disambiguation have proven highly effective when the sense vocabulary is compressed based on the thesaurus hierarchy.
Jeong Yeon Park +2 more
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Efficient estimation of Hindi WSD with distributed word representation in vector space
Journal of King Saud University: Computer and Information Sciences, 2022 Word Sense Disambiguation (WSD) is significant for improving the accuracy of the interpretation of a Natural language text. Various supervised learning-based models and knowledge-based models have been developed in the literature for WSD of the language ...
Archana Kumari, D.K. Lobiyal
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XL-WSD: An Extra-Large and Cross-Lingual Evaluation Framework for Word Sense Disambiguation
AAAI Conference on Artificial Intelligence, 2021 Transformer-based architectures brought a breeze of change to Word Sense Disambiguation (WSD), improving models' performances by a large margin. The fast development of new approaches has been further encouraged by a well-framed evaluation suite for ...
Tommaso Pasini +2 more
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ConSeC: Word Sense Disambiguation as Continuous Sense Comprehension
Conference on Empirical Methods in Natural Language Processing, 2021 Supervised systems have nowadays become the standard recipe for Word Sense Disambiguation (WSD), with Transformer-based language models as their primary ingredient.
Edoardo Barba +2 more
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