Results 21 to 30 of about 84,634 (222)
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
semanticscholar +1 more source
Recent Trends in Word Sense Disambiguation: A Survey
International Joint Conference on Artificial Intelligence, 2021 Word Sense Disambiguation (WSD) aims at making explicit the semantics of a word in context by identifying the most suitable meaning from a predefined sense inventory.
Michele Bevilacqua +3 more
semanticscholar +1 more source
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
doaj +1 more source
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
doaj +1 more source
Nibbling at the Hard Core of Word Sense Disambiguation
Annual Meeting of the Association for Computational Linguistics, 2022 With state-of-the-art systems having finally attained estimated human performance, Word Sense Disambiguation (WSD) has now joined the array of Natural Language Processing tasks that have seemingly been solved, thanks to the vast amounts of knowledge ...
Marco Maru +3 more
semanticscholar +1 more source
A Method of Word Sense Disambiguation with Recurrent Netural Networks
Journal of Harbin University of Science and Technology, 2020 Word sense disambiguation is an important research problem in natural language processing field. For the phenomenon that a Chinese word has many senses, recurrent neural network (RNN) is used to determine true meaning of ambiguous word with its context ...
ZHANG Chunxiang +2 more
doaj +1 more source
Analysis and Evaluation of Language Models for Word Sense Disambiguation
International Conference on Computational Logic, 2021 Transformer-based language models have taken many fields in NLP by storm. BERT and its derivatives dominate most of the existing evaluation benchmarks, including those for Word Sense Disambiguation (WSD), thanks to their ability in capturing context ...
Daniel Loureiro +3 more
semanticscholar +1 more source
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
semanticscholar +1 more source
FEWS: Large-Scale, Low-Shot Word Sense Disambiguation with the Dictionary [PDF]
Conference of the European Chapter of the Association for Computational Linguistics, 2021 Current models for Word Sense Disambiguation (WSD) struggle to disambiguate rare senses, despite reaching human performance on global WSD metrics. This stems from a lack of data for both modeling and evaluating rare senses in existing WSD datasets.
Terra Blevins +2 more
semanticscholar +1 more source
Chinese Word Sense Disambiguation Based on Word translation and Part of speech
Journal of Harbin University of Science and Technology, 2020 For vocabulary ambiguity problem in Chinese, CNN (Convolution Neural Network) is adopted to determine true meaning of ambiguous vocabulary where word, part of speech and translation around its left and right adjacent words are used.
ZHANG Chunxiang +2 more
doaj +1 more source