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Collaboratively authored web contents as resources for word sense disambiguation and discovery
, 2010 openaire +1 more source
Effective Entity Disambiguation in Low-Resource Languages: A Study of Icelandic
2023 IEEE International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT), 2023 Entity disambiguation (ED) is integral to the task of entity linking (EL), the task of identifying named entities in text and linking them to their corresponding entries in a knowledge base (KB).
Valdimar Ágúst Eggertsson +3 more
semanticscholar +3 more sources
Named Entity Disambiguation for Resource-Poor Languages
Proceedings of the Eighth Workshop on Exploiting Semantic Annotations in Information Retrieval, 2015 Named entity disambiguation (NED) is the task of linking ambiguous names in natural language text to canonical entities like people, organizations or places, registered in a knowledge base. The problem is well-studied for English text, but few systems have considered resource-poor languages that lack comprehensive name-entity dictionaries, entity ...
Mohamed H. Gad-Elrab +2 more
semanticscholar +4 more sources
Keyword-Driven Resource Disambiguation over RDF Knowledge Bases
Joint International Conference of Semantic Technology, 2013 Keyword search is the most popular way to access information. In this paper we introduce a novel approach for determining the correct resources for user-supplied queries based on a hidden Markov model. In our approach the user-supplied query is modeled as the observed data and the background knowledge is used for parameter estimation.
Saeedeh Shekarpour +2 more
semanticscholar +5 more sources
Word sense disambiguation for low resource languages: setswana collocations
International Workshop on Signal Processing and Machine Learning (WSPML 2023), 2023 Word sense disambiguation (WSD) is a critical task in natural language processing (NLP) and artificial intelligence. Supervised methods, such as decision list algorithms, are considered the most accurate machine learning algorithms for WSD. However, they
Boago Okgetheng +2 more
semanticscholar +3 more sources
A Novel Approach to Word Sense Disambiguation for a Low-Resource Morphologically Rich Language
Conference Information and Communication Technology, 2022 Ambiguity amongst words is common in every language. Thus in the world of Natural Language Processing(NLP), a very critical problem is one of Word Sense Disambiguation(WSD).
Puberun Boruah
openalex +2 more sources
PosWSD: Low-Resource Word Sense Disambiguation Model using Part Of Speech Information
International Conference on Asian Language Processing, 2022 Word Sense Disambiguation(WSD) is a long-standing problem in Natural Language Processing(NLP), which aims to find the exact meaning of the target word in a given context. Current WSD methods mainly rely on pre-trained models.
Yazhen Chen, Jian Zhang, Qipeng He
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Journal of the Institution of Electronics and Telecommunication Engineers, 2022 Besides word order, word choice is a key stumbling block for machine translation (MT) in morphologically rich languages due to homonyms and polysemous difficulties.
Shefali Saxena +3 more
openalex +2 more sources
Word Sense Disambiguation: Adaptive Word Embedding with Adaptive-Lexical Resource
, 2023 Chandrakant D. Kokane +3 more
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Resources for Nepali Word Sense Disambiguation
2008 International Conference on Natural Language Processing and Knowledge Engineering, 2008Word sense disambiguation (WSD) is a process of identifying proper meaning of words that may have multiple meanings. It is regarded as one of the most challenging problems in the field of natural language processing (NLP). Nepali Language also has words that have multiple meanings, thus giving rise to the problem of WSD in it.
Sanat Kumar Bista +2 more
openaire +2 more sources