Results 41 to 50 of about 84,634 (222)
Annual Meeting of the Association for Computational Linguistics, 2020 Neural architectures are the current state of the art in Word Sense Disambiguation (WSD). However, they make limited use of the vast amount of relational information encoded in Lexical Knowledge Bases (LKB).
Michele Bevilacqua, Roberto Navigli
semanticscholar +1 more source
Hybrid Sense Classification Method for Large-Scale Word Sense Disambiguation
IEEE Access, 2020 Word sense disambiguation (WSD) is a task of determining a reasonable sense of a word in a particular context. Although recent studies have demonstrated some progress in the advancement of neural language models, the scope of research is still such that ...
Yoonseok Heo, Sangwoo Kang, Jungyun Seo
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Improving Japanese Zero Pronoun Resolution by Global Word Sense Disambiguation [PDF]
, 2004 This paper proposes unsupervised word sense disambiguation based on automatically constructed case frames and its incorporation into our zero pronoun resolution system. The word sense disambiguation is applied to verbs and nouns.
Daisuke Kawahara, Sadao Kurohashi
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Conference on Empirical Methods in Natural Language Processing, 2020 Contextualized word embeddings have been employed effectively across several tasks in Natural Language Processing, as they have proved to carry useful semantic information. However, it is still hard to link them to structured sources of knowledge.
Bianca Scarlini +2 more
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A Method of Word Sense Disambiguation with Restricted Boltzmann Machine
Journal of Harbin University of Science and Technology, 2019 For polysemy phenomenon in Chinese, Restricted Boltzmann Machine (RBM) is adopted to determine the true meaning of ambiguous vocabulary where linguistic knowledge in context is used Word form, part of speech and semantic categories in four left and ...
ZHANG Chun-xiang +2 more
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Complexity, 2020 In natural language, the phenomenon of polysemy is widespread, which makes it very difficult for machines to process natural language. Word sense disambiguation is a key issue in the field of natural language processing.
Lei Wang, Qun Ai
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Language Modelling Makes Sense: Propagating Representations through WordNet for Full-Coverage Word Sense Disambiguation [PDF]
Annual Meeting of the Association for Computational Linguistics, 2019 Contextual embeddings represent a new generation of semantic representations learned from Neural Language Modelling (NLM) that addresses the issue of meaning conflation hampering traditional word embeddings.
Daniel Loureiro, A. Jorge
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Improving Data Integration through Disambiguation Techniques [PDF]
, 2008 In this paper Word Sense Disambiguation (WSD) issue in the context of data integration is outlined and an Approximate Word Sense Disambiguation approach (AWSD) is proposed for the automatic lexical annotation of structured and semi-structured data ...
PO, Laura
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Retrieving with good sense [PDF]
, 2000 Although always present in text, word sense ambiguity only recently became regarded as a problem to information retrieval which was potentially solvable.
Sanderson, M.
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Improved Word Sense Disambiguation Using Pre-Trained Contextualized Word Representations [PDF]
Conference on Empirical Methods in Natural Language Processing, 2019 Contextualized word representations are able to give different representations for the same word in different contexts, and they have been shown to be effective in downstream natural language processing tasks, such as question answering, named entity ...
Christian Hadiwinoto +2 more
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