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Beyond Isolation: Multi-Agent Synergy for Improving Knowledge Graph Construction

Hongbin Ye, Honghao Gui, Aijia Zhang, Tong Liu, Weiqiang Jia

Abstract

This paper introduces CooperKGC, a novel framework challenging the conventional solitary approach of large language models (LLMs) in knowledge graph construction (KGC). CooperKGC establishes a collaborative processing network, assembling a team capable of concurrently addressing entity, relation, and event extraction tasks. Experimentation demonstrates that fostering collaboration within CooperKGC enhances knowledge selection, correction, and aggregation capabilities across multiple rounds of interactions.

Beyond Isolation: Multi-Agent Synergy for Improving Knowledge Graph Construction

Abstract

This paper introduces CooperKGC, a novel framework challenging the conventional solitary approach of large language models (LLMs) in knowledge graph construction (KGC). CooperKGC establishes a collaborative processing network, assembling a team capable of concurrently addressing entity, relation, and event extraction tasks. Experimentation demonstrates that fostering collaboration within CooperKGC enhances knowledge selection, correction, and aggregation capabilities across multiple rounds of interactions.
Paper Structure (16 sections, 3 figures, 4 tables, 1 algorithm)

This paper contains 16 sections, 3 figures, 4 tables, 1 algorithm.

Table of Contents

  1. Introduction
  2. Related work
  3. LLM-based Knowledge Graph Construction
  4. Interactive Collaboration of Multiple Agents
  5. Methodology
  6. Construction of Multi-expert Agent Collaboration Network
  7. Customized Expert Knowledge Background.
  8. Collaborative Interaction Optimization
  9. Experiments
  10. Experiment Settings
  11. Dataset.
  12. Baselines.
  13. Performance Comparison with SOTA (RQ1)
  14. Analysis of Team Members and Interaction Rounds (RQ2)
  15. Case Study of Collaboration Process (RQ3)
  16. ...and 1 more sections

Figures (3)

  • Figure 1: The overview of our CooperKGC.
  • Figure 2: Equipping KGC agents with different expert knowledge backgrounds.
  • Figure 3: Micro-F1 Performance with Increased Rounds.