人工知能学会第二種研究会資料
Online ISSN : 2436-5556
文章からの知識グラフ抽出ツールを強化する生成LLM活用
安居 優仁竹内 和広
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研究報告書・技術報告書 フリー

2024 年 2024 巻 SWO-063 号 p. 04-

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In this paper, we extend a tool for extracting knowledge graph candidates by leveraging dependency structure analysis. Specifically, instead of using a dependency structure analysis tool, we replace the syntactic relationship determination based on the derivation rules of one of the wellknown parsing algorithms, the CKY algorithm, with a prompt-based determination using a Large Language Model (LLM). This approach allows a better integration of knowledge graph extraction with syntactic structure analysis. The prompts focus on bunsetsus, the basic units of meaning in Japanese, allowing us to effectively address domain-specific writing styles and handle named entities by restricting sentence sets.

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