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.
@article{arxiv.2310.00637,
title = {Knowledge Engineering using Large Language Models},
author = {Bradley P. Allen and Lise Stork and Paul Groth},
journal= {arXiv preprint arXiv:2310.00637},
year = {2023}
}
Comments
19 pages, 2 figures, accepted in Transactions on Graph Data and Knowledge