An Exploration-Analysis-Disambiguation Reasoning Framework for Word Sense Disambiguation with Low-Parameter LLMs
Abstract
Word Sense Disambiguation (WSD) remains a key challenge in Natural Language Processing (NLP), especially when dealing with rare or domain-specific senses that are often misinterpreted.While modern high-parameter Large Language Models (LLMs) such as GPT-4-Turbo have shown state-of-the-art WSD performance, their computational and energy demands limit scalability.This study investigates whether low-parameter LLMs (
Fields of Study & Subjects
Natural Language Processing Techniques
Topic Modeling
Syntax
Semantics
Linguistic Variation
Publication details
- Journal / source
- Cronfa (Swansea University)
- Publication date
- 1 January 2026
- Language
- EN