目前，我国古籍文献的数字化以文献扫描、粗粒度文件管理等浅层知识服务为主，生成式人工智能技术的发展为古籍文献数字化的深度化提供了新的机遇。文章基于框架语义学理论构建置标语义逻辑结构框架，以生成式逻辑向大语言模型提出问题，递归提取古籍语料中深层语义内容，并将其输出为符合置标语义框架的结构化数据，使古籍文本在基础语义层面获得统一的处理逻辑。古籍自动置标语义框架能够实现大规模自动化古籍文献内容结构生成式表征，为古籍整理智能化转型提供一种自动可行的技术方案。

Currently, the digitalization of ancient Chinese texts primarily involves basic document scanning and coarse-grained file management. However, the development of generative artificial intelligence technologies offers new opportunities for advancing the depth of digitalization of ancient texts. Based on the theory of frame semantics, this article constructs a semantic logical structure framework for semantic tagging. It poses questions to large language models using generative logic, recursively extracts deep semantic content from ancient text corpora, and outputs it as structured data conforming to the semantic tagging framework. This enables ancient texts to be processed with a unified semantic logic at the basic semantic level. The automatic semantic tagging framework for ancient texts can achieve large-scale, automated generative representation of the content structure of ancient documents, providing an automatically viable technical solution for the intelligent transformation of ancient text organization.