用符号学重新理解提示词，揭示其背后的认知与交流机制
The meaning of prompts and the prompts of meaning: Semiotic reflections and modelling
- 基于皮尔斯符号学，将提示视为动态意义生成过程
- 提示词本质是人机共构知识的交流行为，非简单输入指令
- 适合对AI认知机制、信息组织理论感兴趣的学者
本文将大语言模型中的提示（prompt）及其提示行为，视为动态符号现象，借鉴皮尔斯的三元符号模型、九类符号类型及通信的Dynacom模型。研究认为，提示不应仅被视为技术输入，而应被理解为一种涉及符号生成、解释与迭代优化的认知与交际活动。理论基础源于皮尔斯符号学中代表式、对象与解释项之间的互动，以及符号的分类体系：质符、事符、规符；图像符、指示符、象征符；命题、断言、论据，结合Dynacom模型中的解释项三元组。分析表明，大语言模型作为符号资源，会根据用户提示生成解释项，参与共享话语域内的意义建构。研究发现，提示是一种符号化与交际性过程，重塑了数字环境中知识的组织、检索、解读与共建方式。该视角促使我们重新思考计算符号学时代下知识组织与信息搜索的理论与方法基础。
原文摘要 · Abstract (English)
This paper explores prompts and prompting in large language models (LLMs) as dynamic semiotic phenomena, drawing on Peirce's triadic model of signs, his nine sign types, and the Dynacom model of communication. The aim is to reconceptualize prompting not as a technical input mechanism but as a communicative and epistemic act involving an iterative process of sign formation, interpretation, and refinement. The theoretical foundation rests on Peirce's semiotics, particularly the interplay between representamen, object, and interpretant, and the typological richness of signs: qualisign, sinsign, legisign; icon, index, symbol; rheme, dicent, argument - alongside the interpretant triad captured in the Dynacom model. Analytically, the paper positions the LLM as a semiotic resource that generates interpretants in response to user prompts, thereby participating in meaning-making within shared universes of discourse. The findings suggest that prompting is a semiotic and communicative process that redefines how knowledge is organized, searched, interpreted, and co-constructed in digital environments. This perspective invites a reimagining of the theoretical and methodological foundations of knowledge organization and information seeking in the age of computational semiosis
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