Knowledge Engineering using Large Language Models
Bradley P. Allen Lise Stork Paul Groth
Knowledge engineering is a discipline that focuses on the creation and
maintenance of processes that generate and apply knowledge. Traditionally,
knowledge engineering approaches have focused on knowledge expressed in formal
languages. The emergence of large language models and their capabilities to
effectively work with natural language, in its broadest sense, raises questions
about the foundations and practice of knowledge engineering. Here, we outline
the potential role of LLMs in knowledge engineering, identifying two central
directions: 1) creating hybrid neuro-symbolic knowledge systems; and 2)
enabling knowledge engineering in natural language. Additionally, we formulate
key open research questions to tackle these directions.