arXiv:2411.09601cs.AI2024-11被引 47
用大模型加速知识图谱与本体工程，提升建模与维护效率。
Accelerating Knowledge Graph and Ontology Engineering with Large Language Models
- 利用大模型自动化完成本体建模、扩展与实体消歧。
- 模块化本体设计是实现高效工程的核心方法。
- 适合从事知识图谱构建与智能系统开发的研究者。
大型语言模型有望显著加速知识图谱与本体工程中的关键任务，包括本体建模、扩展、修改、填充、对齐以及实体消歧。本文将基于大模型的知识图谱与本体工程定位为一个新兴且重要的研究方向，并强调模块化本体方法的中心地位。
原文摘要 · Abstract (English)
Large Language Models bear the promise of significant acceleration of key Knowledge Graph and Ontology Engineering tasks, including ontology modeling, extension, modification, population, alignment, as well as entity disambiguation. We lay out LLM-based Knowledge Graph and Ontology Engineering as a new and coming area of research, and argue that modular approaches to ontologies will be of central importance.
知识图谱大模型本体工程
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