Proposal for a Classification and Ordering Method for Manual Sentences Using a Large-Scale Linguistic Model

Abstract

When creating manuals, it is important to design a table of contents (TOC) that makes it easy for users to find the necessary information. However, constructing a TOC based on the users' perspective is not straightforward, requiring specialized knowledge. To solve this problem, this study proposes an automatic TOC generation method using large language models. Specifically, we design prompts that incorporate the rules and expertise used by manual creation professionals, thereby generating a TOC structure in which users can easily find information. We compared the table of contents structure generated by the proposed method with the existing table of contents structure, and confirmed that it is equivalent to the structure created by experts. Furthermore, through the experiments conducted in this paper, we discuss the method’s potential to automatically generate a generic TOC structure, as well as possible directions for further enhancement.