Computer Science

Computer Science ›› 2025, Vol. 52 ›› Issue (1): 1-33.doi: 10.11896/jsjkx.240100109

• Technology Research and Application of Large Language Model • Previous Articles     Next Articles

Survey of Research on Knowledge Graph Based on Pre-trained Language Models

ZENG Zefan1,2,3, HU Xingchen1,2, CHENG Qing1,2, SI Yuehang1,2, LIU Zhong1,2   

  1. 1 College of Systems Engineering,National University of Defense Technology,Changsha 410073,China
    2 Laboratory for Big Data and Decision,National University of Defense Technology,Changsha 410073,China
    3 Fujian Provincial Military Command,Fuzhou 350001,China
  • Received:2024-01-12 Revised:2024-03-07 Online:2025-01-15 Published:2025-01-09
  • About author:ZENG Zefan,born in 1993, Ph.D candidate.His main research interests include pre-trained language model and knowledge reasoning.
    HU Xingchen,born in 1989, Ph.D, associate professor.His main research interests include machine learning,evolutionary optimization and target engineering.
  • Supported by:
    National Natural Science Foundation of China(62376279).

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Abstract: In the era of large language models(LLMs),knowledge graphs(KGs),as a structured representation of knowledge,play an irreplaceable role in enhancing the reliability,security,and interpretability of artificial intelligence.With its superior performance in semantic understanding,pre-trained language models(PLMs) have become the main approach in knowledge graph research in recent years.This paper systematically reviews the research works on PLM-based knowledge graphs,including know-ledge graph construction,representation learning,reasoning,and question answering.The core ideas of the relevant models and methods are introduced and a classification system is established based on the technological approaches.A comparative analysis of the advantages and disadvantages of different categories of methods is provided.In addition,the application status of pre-trained language models in two new types of knowledge graphs,event knowledge graphs and multimodal knowledge graphs,is reviewed.Finally,the challenges faced by current research on knowledge graphs based on pre-trained language models are summarized,and future research directions are prospected.

Key words: Knowledge graph, Pre-trained language model, Large language model, Multi-modal, Event knowledge graph

CLC Number: 

  • TP182
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