Homonym Sense Disambiguation in the Georgian Language

arXiv:2405.00710v1 Announce Type: new
Abstract: This research proposes a novel approach to the Word Sense Disambiguation (WSD) task in the Georgian language, based on supervised fine-tuning of a pre-trained Large Language Model (LLM) on a dataset formed by filtering the Georgian Common Crawls corpus. The dataset is used to train a classifier for words with multiple senses. Additionally, we present experimental results of using LSTM for WSD. Accurately disambiguating homonyms is crucial in natural language processing. Georgian, an agglutinative language …

abstract arxiv classifier cs.cl cs.lg dataset filtering fine-tuning language language model large language large language model llm novel research sense supervised fine-tuning train type word