Results 1 to 10 of about 1,880,945 (215)

Contrastive Learning for Morphological Disambiguation Using Large Language Models in Low-Resource Settings

Applied Sciences
In this paper, a contrastive learning approach for morphological disambiguation (MD) using large language models (LLMs) is presented. A contrastive loss function is introduced for training the approach, which reduces the distance between the correct ...
Gulmira Tolegen, Alymzhan Toleu, Rustam Mussabayev   +2 more
doaj   +3 more sources

Hybrid Transformer-Based Large Language Models for Word Sense Disambiguation in the Low-Resource Sesotho sa Leboa Language [PDF]

Applied Sciences
This study addresses a lexical ambiguity issue in Sesotho sa Leboa that arises from terms with various meanings, often known as homonyms or polysemous words.
Hlaudi Daniel Masethe, Mosima Anna Masethe, Sunday O. Ojo, Pius A. Owolawi, Fausto Giunchiglia   +4 more
doaj   +3 more sources

Word Sense Disambiguation for Morphologically Rich Low-Resourced Languages: A Systematic Literature Review and Meta-Analysis

Information
In natural language processing, word sense disambiguation (WSD) continues to be a major difficulty, especially for low-resource languages where linguistic variation and a lack of data make model training and evaluation more difficult.
Hlaudi Daniel Masethe, Mosima Anna Masethe, Sunday Olusegun Ojo, Fausto Giunchiglia, Pius Adewale Owolawi   +4 more
doaj   +3 more sources

Minimalist Entity Disambiguation for Mid-Resource Languages [PDF]

SUSTAINLP, 2023
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Benno Kruit
openalex   +2 more sources

Exploiting a lexical resource for discourse connective disambiguation in German [PDF]

International Conference on Computational Linguistics, 2020
In this paper we focus on connective identification and sense classification for explicit discourse relations in German, as two individual sub-tasks of the overarching Shallow Discourse Parsing task.
Peter Bourgonje, Manfred Stede
openalex   +2 more sources

Unsupervised Named Entity Disambiguation for Low Resource Domains [PDF]

Conference on Empirical Methods in Natural Language Processing
In the ever-evolving landscape of natural language processing and information retrieval, the need for robust and domain-specific entity linking algorithms has become increasingly apparent.
D. V. Datta, Soumajit Pramanik
semanticscholar   +3 more sources

A Literature Survey on Word Sense Disambiguation for the Hindi Language

Information, 2023
Word sense disambiguation (WSD) is a process used to determine the most appropriate meaning of a word in a given contextual framework, particularly when the word is ambiguous.
Vinto Gujjar, Neeru Mago, Raj Kumari, Shrikant Patel, Nalini Chintalapudi, Gopi Battineni   +5 more
doaj   +2 more sources

Data sets for author name disambiguation: an empirical analysis and a new resource [PDF]

Scientometrics, 2017
Data sets of publication meta data with manually disambiguated author names play an important role in current author name disambiguation (AND) research.
Mark-Christoph Müller, Florian Reitz, Nicolas Roy   +2 more
openalex   +2 more sources

Word Sense Disambiguation in Native Spanish: A Comprehensive Lexical Evaluation Resource [PDF]

arXiv.org
Human language, while aimed at conveying meaning, inherently carries ambiguity. It poses challenges for speech and language processing, but also serves crucial communicative functions.
Pablo Ortega, Jordi Luque, Luis Lamiable, Rodrigo López, Richard Benjamins   +4 more
openalex   +2 more sources

Clarifying terminology and definitions in education services for mental health users: A disambiguation study. [PDF]

PLoS One
In the wake of the mental health crisis in children and adolescents, the coordination of education and mental health services has become a global priority.
Pokhilenko I, Gutierrez-Colosia MR, Janssen LMM, Evers SMAA, Paulus ATG, Drost RMWA, Campoy-Muñoz P, Simon J, Salvador-Carulla L.   +8 more
europepmc   +2 more sources