2023/12/01 by B.P.; id_orcid 0000-0003-0216-3930 Allen, Allen, Bradley P., L. Stork +3
Computer Science · Social Sciences · #Computing methodologies → Machine learning #Computing methodologies → Natural language processing #Computing methodologies → Philosophical/theoretical foundations of artificial intelligence #Language and cultural evolution #Natural Language Processing Techniques #Software and its engineering → Software development methods #Topic Modeling #knowledge engineering #large language models
paper · pdf · doi:10.4230/tgdk.1.1.3
openalex publication_date 2023/12/01 · openalex created_date 2026/03/15 · openalex updated_date 2026/07/02
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.