Large Language Models and Knowledge Graphs: Opportunities and Challenges

Open Access
Authors
  • J. Chen
  • S. Dietze
  • H. Jabeen
  • J. Omeliyanenko
  • W. Zhang
  • M. Lissandrini
  • R. Biswas
  • G. de Melo
  • A. Bonifati
  • E. Vakaj
  • M. Dragoni
  • D. Graux
Publication date 12-2023
Journal Transactions on Graph Data and Knowledge
Article number 2
Volume | Issue number 1 | 1
Number of pages 38
Organisations
  • Faculty of Science (FNWI) - Informatics Institute (IVI)
Abstract Large Language Models (LLMs) have taken Knowledge Representation - and the world - by storm. This inflection point marks a shift from explicit knowledge representation to a renewed focus on the hybrid representation of both explicit knowledge and parametric knowledge. In this position paper, we will discuss some of the common debate points within the community on LLMs (parametric knowledge) and Knowledge Graphs (explicit knowledge) and speculate on opportunities and visions that the renewed focus brings, as well as related research topics and challenges.
Document type Article
Note In Special Issue on Trends in Graph Data and Knowledge
Language English
Published at https://doi.org/10.4230/TGDK.1.1.2
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Large Language Models and Knowledge Graphs (Final published version)
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