Ontology Learning

Ontology learning (OL) focuses on automatically extracting and structuring knowledge from text to create ontologies—formal representations of knowledge. Current research heavily utilizes large language models (LLMs), exploring both their intrinsic capabilities and the benefits of incorporating external knowledge sources like WordNet to improve performance on tasks such as relation extraction and taxonomy discovery. This field is significant because automated ontology creation can streamline knowledge organization across diverse domains, improving data interoperability and facilitating more sophisticated AI systems. Furthermore, research is actively investigating how to best leverage ontological information to enhance machine learning models, particularly in scenarios with noisy or incomplete data.