Word Sense Disambiguation

Word sense disambiguation (WSD) aims to automatically determine the correct meaning of a word within a given context, a crucial step in natural language processing. Current research focuses on improving supervised models, often leveraging semantic lexical resources like WordNet and incorporating advanced architectures such as recurrent neural networks and transformers, sometimes enhanced with neurosymbolic methods. These advancements are driving progress in WSD across multiple languages, including Arabic and Spanish, with a particular emphasis on improving accuracy and efficiency, particularly in resource-constrained settings and cross-lingual applications. The resulting improvements have significant implications for various applications, including machine translation, information retrieval, and text summarization.