Results 21 to 30 of about 83,244 (255)
Word sense disambiguation for event trigger word detection in biomedicine [PDF]
BMC Bioinformatics, 2011 This paper describes a method for detecting event trigger words in biomedical text based on a word sense disambiguation (WSD) approach. We first investigate the applicability of existing WSD techniques to trigger word disambiguation in the BioNLP 2009 ...
Martinez David, Baldwin Timothy
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Word sense disambiguation criteria [PDF]
Proceedings of the 20th international conference on Computational Linguistics - COLING '04, 2004 This article describes the results of a systematic in-depth study of the criteria used for word sense disambiguation. Our study is based on 60 target words: 20 nouns, 20 adjectives and 20 verbs. Our results are not always in line with some practices in the field.
Audibert, Laurent
openaire +7 more sources
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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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
exaly +2 more sources
Entity Linking meets Word Sense Disambiguation: a Unified Approach
Transactions of the Association for Computational Linguistics, 2021 Entity Linking (EL) and Word Sense Disambiguation (WSD) both address the lexical ambiguity of language. But while the two tasks are pretty similar, they differ in a fundamental respect: in EL the textual mention can be linked to a named entity which may ...
Andrea Moro +2 more
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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
semanticscholar +1 more source
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
semanticscholar +1 more source
Research on Unsupervised Word Sense Disambiguation [PDF]
Journal of Software, 2009 Ruiqin Wang, Fansheng Kong
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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
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
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