Results 51 to 60 of about 58,551 (288)
Memory-Based Word Sense Disambiguation [PDF]
Computers and the Humanities, 2000 We describe a memory-based classification architecture for word sense disambiguation and its application to the SENSEVAL evaluation task. For each ambiguous word, a semantic word expert is automatically trained using a memory-based approach. In each expert, selecting the correct sense of a word in a new context is achieved by finding the closest match ...
Veenstra, J. +4 more
openaire +6 more sources
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
semanticscholar +1 more source
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
semanticscholar +1 more source
Graph Convolutional Network for Word Sense Disambiguation
Discrete Dynamics in Nature and Society, 2021 Word sense disambiguation (WSD) is an important research topic in natural language processing, which is widely applied to text classification, machine translation, and information retrieval.
Chun-Xiang Zhang +3 more
doaj +1 more source
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
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
doaj +1 more source
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
doaj +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 definitions (or glosses) of the ...
Yang Song, Xin Cai Ong, H. Ng, Qian Lin
semanticscholar +1 more source
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
doaj +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