Results 31 to 40 of about 82,228 (264)
ConSeC: Word Sense Disambiguation as Continuous Sense Comprehension
Conference on Empirical Methods in Natural Language Processing, 2021 Supervised systems have nowadays become the standard recipe for Word Sense Disambiguation (WSD), with Transformer-based language models as their primary ingredient.
Edoardo Barba +2 more
semanticscholar +1 more source
Chinese Word Sense Disambiguation Based on Word translation and Part of speech
Journal of Harbin University of Science and Technology, 2020 For vocabulary ambiguity problem in Chinese, CNN (Convolution Neural Network) is adopted to determine true meaning of ambiguous vocabulary where word, part of speech and translation around its left and right adjacent words are used.
ZHANG Chunxiang +2 more
doaj +1 more source
SBU-WSD-Corpus: A Sense Annotated Corpus for Persian All-words Word Sense Disambiguation [PDF]
International Journal of Web Research, 2022 Word Sense Disambiguation (WSD) is a long standing task in Natural Language Processing (NLP) that aims to automatically identify the most relevant meaning of the words in a given context.
Hossein Rouhizadeh +2 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
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
semanticscholar +1 more source
Word sense disambiguation in queries [PDF]
Proceedings of the 14th ACM international conference on Information and knowledge management, 2005 This paper presents a new approach to determine the senses of words in queries by using WordNet. In our approach, noun phrases in a query are determined first. For each word in the query, information associated with it, including its synonyms, hyponyms, hypernyms, definitions of its synonyms and hyponyms, and its domains, can be used for word sense ...
Shuang Liu, Clement Yu, Weiyi Meng
openaire +2 more sources
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
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
semanticscholar +1 more source
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
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