Leveraging Large Language Models for Generating Research Topic Ontologies: A Multi-Disciplinary Study
Researchers explored how large language models can generate research topic ontologies across biomedicine, physics, and engineering. They introduced PEM-Rel-8K, a dataset of over 8,000 relationships from MeSH, PhySH, and IEEE taxonomies. Experiments showed that fine-tuning LLMs on this dataset significantly improved their ability to identify semantic relationships and transfer knowledge between disciplines. AI
IMPACT LLMs can automate the creation of structured knowledge bases, improving scientific information retrieval and management.