Results 11 to 20 of about 54,249 (180)
GlossBERT: BERT for Word Sense Disambiguation with Gloss Knowledge [PDF]
Conference on Empirical Methods in Natural Language Processing, 2019 Word Sense Disambiguation (WSD) aims to find the exact sense of an ambiguous word in a particular context. Traditional supervised methods rarely take into consideration the lexical resources like WordNet, which are widely utilized in knowledge-based ...
Luyao Huang +3 more
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Word Sense Disambiguation [PDF]
, 2012 Word-sense disambiguation (WSD) is the process of identifying the meanings of words in context. This article begins with discussing the origins of the problem in the earliest machine translation systems. Early attempts to solve the WSD problem suffered from a lack of coverage.
Mark Stevenson, Yorick Wilks
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Comparative Analysis of Recurrent Neural Network Architectures for Arabic Word Sense Disambiguation
International Conference on Web Information Systems and Technologies, 2022 : Word Sense Disambiguation (WSD) refers to the process of discovering the correct sense of an ambiguous word occurring in a given context. In this paper, we address the problem of Word Sense Disambiguation of low-resource languages such as Arabic ...
R. Saidi, Fethi Jarray, M. Alsuhaibani
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DiBiMT: A Novel Benchmark for Measuring Word Sense Disambiguation Biases in Machine Translation
Annual Meeting of the Association for Computational Linguistics, 2022 Lexical ambiguity poses one of the greatest challenges in the field of Machine Translation. Over the last few decades, multiple efforts have been undertaken to investigate incorrect translations caused by the polysemous nature of words.
Niccolò Campolungo +3 more
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Transfer Learning and Augmentation for Word Sense Disambiguation [PDF]
European Conference on Information Retrieval, 2021 Many downstream NLP tasks have shown significant improvement through continual pre-training, transfer learning and multi-task learning. State-of-the-art approaches in Word Sense Disambiguation today benefit from some of these approaches in conjunction ...
Harsh Kohli
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Role of Genetic Algorithm in Optimization of Hindi Word Sense Disambiguation
IEEE Access, 2022 The Word Sense Disambiguation system is widely used in many fields, including business, research, education, and government organizations. The availability of natural language data on the internet has grown in tandem with the rapid advancement of ...
Surbhi Bhatia +2 more
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Framing Word Sense Disambiguation as a Multi-Label Problem for Model-Agnostic Knowledge Integration
Conference of the European Chapter of the Association for Computational Linguistics, 2021 Recent studies treat Word Sense Disambiguation (WSD) as a single-label classification problem in which one is asked to choose only the best-fitting sense for a target word, given its context.
Simone Conia, Roberto Navigli
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Unsupervised Word Sense Disambiguation Rivaling Supervised Methods
Annual Meeting of the Association for Computational Linguistics, 1995 This paper presents an unsupervised learning algorithm for sense disambiguation that, when trained on unannotated English text, rivals the performance of supervised techniques that require time-consuming hand annotations.
David Yarowsky
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Word Sense Disambiguation: A Survey
International Journal of Control Theory and Computer Modeling, 2015 In this paper, we made a survey on Word Sense Disambiguation (WSD). Near about in all major languages around the world, research in WSD has been conducted upto different extents. In this paper, we have gone through a survey regarding the different approaches adopted in different research works, the State of the Art in the performance in this domain ...
Pal, Alok Ranjan, Saha, Diganta
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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
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