Year: 2024
Type: conference-paper
Abstract: The report presents the evaluation results of our approach in the LLM4OL Challenge, where we fine-tuned GPT-3.5 for Task A (Term Typing) across three different datasets. Our approach demonstrated consistent and robust performance during few- shot testing, achieving top rankings in several datasets and sub-datasets, proving the potential of fine-tuning LLMs for ontology creation tasks.
Source: Open Conference Proceedings
Institution: Kansas State University
Language: English
Topic: Semantic Web and Ontologies
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
Funder: National Science Foundation
OpenAlex ID: W4403071392