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

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   +2 more sources

Leveraging large language models for rare disease named entity recognition. [PDF]

PLOS Digital Health
Named Entity Recognition (NER) in the rare disease domain poses unique challenges due to limited labeled data, semantic ambiguity between entity types, and long-tail distributions.
Nan Miles Xi, Yu Deng, Lin Wang
doaj   +2 more sources

A comprehensive dataset for Arabic word sense disambiguation [PDF]

Data in Brief
This data paper introduces a comprehensive dataset tailored for word sense disambiguation tasks, explicitly focusing on a hundred polysemous words frequently employed in Modern Standard Arabic.
Sanaa Kaddoura, Reem Nassar
doaj   +2 more sources

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

Human language, while aimed at conveying meaning, inherently carries ambiguity. It poses challenges for speech and language processing, but also serves crucial communicative functions. Efficiently solve ambiguity is both a desired and a necessary characteristic.
Pablo Ortega, Jordi Luque, Luis Lamiable, Rodrigo López, Richard Benjamins   +4 more
openalex   +3 more sources

AI-Driven Medical Device Risk Management: A New Paradigm Integrating Large Language Models and Prompt Engineering for Standard-Risk Knowledge Graph Construction and Application [PDF]

Risk Management and Healthcare Policy
Wanting Zhu,1 Peiming Zhang,1 Wenke Xia,1 Ziming Gao,2 Weiqi Li,1 Ruixue Tian,3 Li Wang4 1School of Health Science and Engineering, University of Shanghai for Science and Technology, Educational Institution, Shanghai, People’s Republic of China ...
Zhu W, Zhang P, Xia W, Gao Z, Li W, Tian R, Wang L   +6 more
doaj   +2 more sources

Leveraging Semantic Diffusion for Polysemous Word Disambiguation in Morphologically Rich Low-resourced Languages [PDF]

Contemporary Research Analysis Journal
Word Sense Disambiguation (WSD) remains one of the most challenging problems in Natural Language Processing (NLP), particularly in morphologically rich and low-resource languages. Hausa presents a unique case, where polysemy interacts with morphology to produce highly ambiguous tokens.
Halima Aminu, Ibrahim Saidu, Philip O. Odion   +2 more
openalex   +2 more sources

Building a Multilingual Lexical Resource for Named Entity Disambiguation, Translation and Transliteration

, 2008
In this paper, we present HeiNER, the multilingual Heidelberg Named Entity Resource. HeiNER contains 1,547,586 disambiguated English Named Entities together with translations and transliterations to 15 languages. Our work builds on the approach described in (Bunescu and Pasca, 2006), yet extends it to a multilingual dimension.
Wolodja Wentland, Johannes Knopp, Carina Silberer, Matthias Härtung   +3 more
  +5 more sources

PubMed Computed Authors in 2024: an open resource of disambiguated author names in biomedical literature. [PDF]

Bioinformatics
Abstract Summary Over 55% of author names in PubMed are ambiguous: the same name is shared by different individual researchers. This poses significant challenges on precise literature retrieval for author name queries, a common behavior in biomedical literature search.
Tian S, Chen Q, Comeau DC, Wilbur WJ, Lu Z.   +4 more
europepmc   +3 more sources

Sentiment analysis techniques, challenges, and opportunities: Urdu language-based analytical study [PDF]

PeerJ Computer Science, 2022
Sentiment analysis in research involves the processing and analysis of sentiments from textual data. The sentiment analysis for high resource languages such as English and French has been carried out effectively in the past. However, its applications are
Muhammad Irzam Liaqat, Muhammad Awais Hassan, Muhammad Shoaib, Syed Khaldoon Khurshid, Mohamed A. Shamseldin   +4 more
doaj   +2 more sources

Efficient estimation of Hindi WSD with distributed word representation in vector space

Journal of King Saud University: Computer and Information Sciences, 2022
Word Sense Disambiguation (WSD) is significant for improving the accuracy of the interpretation of a Natural language text. Various supervised learning-based models and knowledge-based models have been developed in the literature for WSD of the language ...
Archana Kumari, D.K. Lobiyal
doaj   +1 more source