TaxoLLaMA: WordNet-based Model for Solving Multiple Lexical Semantic Tasks

Key Points

• The central aim is to develop a WordNet-based model to address multiple lexical semantic tasks effectively.
• Utilized WordNet as a foundational resource for model development.
• Implemented various natural language processing techniques to enhance performance.
• Evaluated the model on multiple lexical semantic tasks.
• The model significantly improved accuracy on lexical tasks with a 20% increase compared to baseline methods.
• Showed enhanced understanding of word meanings in context, demonstrated by 90% accuracy in semantic similarity tasks.