Results 51 to 60 of about 82,228 (264)
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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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
semanticscholar +1 more source
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.
core +2 more sources
AMuSE-WSD: An All-in-one Multilingual System for Easy Word Sense Disambiguation
Conference on Empirical Methods in Natural Language Processing, 2021 Over the past few years, Word Sense Disambiguation (WSD) has received renewed interest: recently proposed systems have shown the remarkable effectiveness of deep learning techniques in this task, especially when aided by modern pretrained language models.
Riccardo Orlando +4 more
semanticscholar +1 more source
Improved Word Sense Disambiguation with Enhanced Sense Representations
Conference on Empirical Methods in Natural Language Processing, 2021 Current state-of-the-art supervised word sense disambiguation (WSD) systems (such as GlossBERT and bi-encoder model) yield sur-prisingly good results by purely leveraging pre-trained language models and short dictionary deļ¬nitions (or glosses) of the ...
Yang Song, Xin Cai Ong, H. Ng, Qian Lin
semanticscholar +1 more source
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
semanticscholar +1 more source
Annual Meeting of the Association for Computational Linguistics, 2021 Lately proposed Word Sense Disambiguation (WSD) systems have approached the estimated upper bound of the task on standard evaluation benchmarks. However, these systems typically implement the disambiguation of words in a document almost independently ...
Ming Wang, Yinglin Wang
semanticscholar +1 more source
Interpretability in Word Sense Disambiguation using Tsetlin Machine
International Conference on Agents and Artificial Intelligence, 2021 : Word Sense Disambiguation (WSD) is a longstanding unresolved task in Natural Language Processing. The challenge lies in the fact that words with the same spelling can have completely different senses, sometimes depending on subtle characteristics of ...
Rohan Kumar Yadav +3 more
semanticscholar +1 more source
Adapting BERT for Word Sense Disambiguation with Gloss Selection Objective and Example Sentences [PDF]
Findings, 2020 Domain adaptation or transfer learning using pre-trained language models such as BERT has proven to be an effective approach for many natural language processing tasks.
Boon Peng Yap +2 more
semanticscholar +1 more source
Word sense disambiguation and information retrieval [PDF]
, 1994 It has often been thought that word sense ambiguity is a cause of poor performance in Information Retrieval (IR) systems. The belief is that if ambiguous words can be correctly disambiguated, IR performance will increase.
Sanderson, M.
core +1 more source