基于大语言模型(LLM)的宝石知识图谱的构建

Construction of Gem Knowledge Graph Based on Large Language Model

  • 摘要: 宝石学知识的来源有书籍、期刊、课程、市场等,宝石知识点繁多且在存储上处于相对孤立的状态,不利于从业者和研究者检索知识,图谱能够处理知识点之间的复杂关联,是常用的结构化数据无法实现的,构建图谱形式的宝石知识库系统可以方便学习和检索。本文介绍了传统的知识图谱构建方法并指出了其中的难点(成本高、工作量大、技术难、容易出错),提出了使用大语言模型(LLM)来完成知识图谱构建中的一些任务来改善成本和工作量的问题;构思了一种基于LLM的知识图谱构建思路(步骤包括数据清洗、知识获取和知识精炼),构建了一个能够覆盖本科阶段宝石知识的宝石知识图谱,对一些查询场景做了展示,经过内部测试评估证明了新方法的可行性和高效率,并展望了该图谱未来可能的应用方向。

     

    Abstract: The sources of gemmological knowledge include books, journals, courses, markets and related disciplines. A complete gemmological knowledge system is of great significance to the jewelry industry. Gem knowledge points are numerous and relatively isolated in storage, which is not conducive to practitioners and researchers to retrieve knowledge. This problem can be solved by constructing a gem knowledge base system. The graph can deal with the complex association between knowledge points, which is impossible for widely used structured database, therefore, a knowledge base in the form of a knowledge graph is selected. This paper introduces the traditional knowledge graph construction method and points out the difficulties: high cost, heavy workload, difficult technology and slightly low accuracy. It is proposed to use LLM (Large language model) to complete some tasks in knowledge graph construction to improve the cost and workload. A new knowledge graph construction idea based on LLM is conceived. Its steps include data cleaning, knowledge acquisition and knowledge refinement. According to the above ideas, a gemstone knowledge graph that can cover the gemstone knowledge of the bachelor stage is constructed, and some query scenarios are displayed. The feasibility and high efficiency of the new method are proved by our test evaluation, and the possible application direction of the graph is prospected.

     

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