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ACM Computing Surveys, 2009
Word sense disambiguation (WSD) is the ability to identify the meaning of words in context in a computational manner. WSD is considered an AI-complete problem, that is, a task whose solution is at least as hard as the most difficult problems in artificial intelligence.
Roberto Navigli
exaly +5 more sources
Word sense disambiguation (WSD) is the ability to identify the meaning of words in context in a computational manner. WSD is considered an AI-complete problem, that is, a task whose solution is at least as hard as the most difficult problems in artificial intelligence.
Roberto Navigli
exaly +5 more sources
Non-Parametric Word Sense Disambiguation for Historical Languages
NLP4DH, 2022Recent approaches to Word Sense Disambiguation (WSD) have profited from the enhanced contextualized word representations coming from contemporary Large Language Models (LLMs).
Enrique Manjavacas Arevalo +1 more
semanticscholar +1 more source
2013
This chapter discusses the basic concepts of Word Sense Disambiguation (WSD) and the approaches to solving this problem. Both general purpose WSD and domain specific WSD are presented. The first part of the discussion focuses on existing approaches for WSD, including knowledge-based, supervised, semi-supervised, unsupervised, hybrid, and bilingual ...
Pushpak Bhattacharyya, Mitesh Khapra
+5 more sources
This chapter discusses the basic concepts of Word Sense Disambiguation (WSD) and the approaches to solving this problem. Both general purpose WSD and domain specific WSD are presented. The first part of the discussion focuses on existing approaches for WSD, including knowledge-based, supervised, semi-supervised, unsupervised, hybrid, and bilingual ...
Pushpak Bhattacharyya, Mitesh Khapra
+5 more sources
WIREs Data Mining Knowl. Discov., 2022
In communication, textual data are a vital attribute. In all languages, ambiguous or polysemous words' meaning changes depending on the context in which they are used.
S. Kaddoura, Rowanda D. Ahmed, J. D.
semanticscholar +1 more source
In communication, textual data are a vital attribute. In all languages, ambiguous or polysemous words' meaning changes depending on the context in which they are used.
S. Kaddoura, Rowanda D. Ahmed, J. D.
semanticscholar +1 more source
Word sense disambiguation for Turkish
2009 24th International Symposium on Computer and Information Sciences, 2009Word Sense Disambiguation (WSD) is the core and one of the hardest problems of many Natural Language Processing tasks. WSD is considered as an AI-complete problem. Although there are many approaches trying to solve this problem, many of them are not adequate to solve WSD problem for Turkish.
Mert, Ezgi, Dalkılıç, Gökhan
openaire +2 more sources
Sense Space for Word Sense Disambiguation
2018 IEEE International Conference on Big Data and Smart Computing (BigComp), 2018Word sense disambiguation is essential for semantic analysis in many natural language-related applications, such as information retrieval, data mining, and machine translation. One of the effective models for word sense disambiguation is the word space model that represents context vectors and sense vectors in a word vector space.
Myung Yun Kang +2 more
openaire +1 more source
Global WordNet Conference, 2019
In this article, we tackle the issue of the limited quantity of manually sense annotated corpora for the task of word sense disambiguation, by exploiting the semantic relationships between senses such as synonymy, hypernymy and hyponymy, in order to ...
Loïc Vial, B. Lecouteux, D. Schwab
semanticscholar +1 more source
In this article, we tackle the issue of the limited quantity of manually sense annotated corpora for the task of word sense disambiguation, by exploiting the semantic relationships between senses such as synonymy, hypernymy and hyponymy, in order to ...
Loïc Vial, B. Lecouteux, D. Schwab
semanticscholar +1 more source
2018
Word sense disambiguation (WSD) is the process of identifying the meanings of words in context. The difficulty of this problem stems from the subtlety of word sense differences and the need for some level of understanding. This chapter describes the main approaches to the problem, methods for evaluating performance, and potential applications.
Eneko Agirre, Mark Stevenson
openaire +1 more source
Word sense disambiguation (WSD) is the process of identifying the meanings of words in context. The difficulty of this problem stems from the subtlety of word sense differences and the need for some level of understanding. This chapter describes the main approaches to the problem, methods for evaluating performance, and potential applications.
Eneko Agirre, Mark Stevenson
openaire +1 more source