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LogNER: Enhancing log semantics with LLM-driven entity recognition

delete2026-04-16
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PRE
AI
C
Chentong Zhao
J
Jinpeng Xiang
L
Lixin Zhao *
A
Aimin Yu
L
Lijun Cai
D
Dan Meng
DOI:10.1016/j.jss.2026.112892delete
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Abstract

Abstract

En 中文
• Establishes log entity recognition as a missing semantic dimension in existing log analysis. • Proposes the LogNER framework combining template-assisted and LLM-driven recognition. • Experiments on four heterogeneous datasets demonstrate strong effectiveness and generalization. • Ablation results confirm each core component’s essential contribution to overall performance.
Keywords:
Log entity recognition
Log analysis
Large Language Models
Entity recognition
LogNER framework

Journal

Journal of Systems and Software cover
Journal of Systems and Software
IF:
4.1
Papers:
5.4K
Citations:
8.4K

Organization

C
Chinese Academy of Sciences
Scholars:
3.9W
Papers: 1.5W
Citations: 58.4W