Northrop Frye's theory of four fundamental narrative genres (comedy, romance, tragedy, satire) has profoundly influenced literary criticism, yet computational approaches to his framework have focused primarily on narrative patterns rather than character functions. In this paper, we present a new character function framework that complements pattern-based analysis by examining how archetypal roles manifest differently across Frye's genres. Drawing on Jungian archetype theory, we derive four universal character functions (protagonist, mentor, antagonist, companion) by mapping them to Jung's psychic structure components. These functions are then specialized into sixteen genre-specific roles based on prototypical works. To validate this framework, we conducted a multi-model study using six state-of-the-art Large Language Models (LLMs) to evaluate character-role correspondences across 40 narrative works. The validation employed both positive samples (160 valid correspondences) and negative samples (30 invalid correspondences) to evaluate whether models both recognize valid correspondences and reject invalid ones. LLMs achieved substantial performance (mean balanced accuracy of 82.5%) with strong inter-model agreement (Fleiss' $κ$ = 0.600), demonstrating that the proposed correspondences capture systematic structural patterns. Performance varied by genre (ranging from 72.7% to 89.9%) and role (52.5% to 99.2%), with qualitative analysis revealing that variations reflect genuine narrative properties, including functional distribution in romance and deliberate archetypal subversion in satire. This character-based approach demonstrates the potential of LLM-supported methods for computational narratology and provides a foundation for future development of narrative generation methods and interactive storytelling applications.

翻译：诺斯罗普·弗莱关于四种基本叙事体裁（喜剧、传奇、悲剧、讽刺）的理论对文学批评产生了深远影响，然而针对其框架的计算方法主要集中于叙事模式而非人物功能。本文提出一种新的人物功能框架，通过考察原型角色在弗莱各体裁中的不同呈现方式，对基于模式的分析形成补充。借鉴荣格的原型理论，我们通过将其映射至荣格心理结构成分，推导出四种普适性人物功能（主角、导师、反派、同伴）。基于典型作品，这些功能进一步细化为十六种体裁专属角色。为验证该框架，我们采用六种前沿大型语言模型（LLMs）开展多模型研究，评估了涵盖40部叙事作品的人物-角色对应关系。验证过程同时使用正样本（160个有效对应）与负样本（30个无效对应），以评估模型能否既识别有效对应又拒绝无效对应。LLMs取得了显著性能表现（平均平衡准确率达82.5%）且模型间一致性较强（弗莱斯$κ$ = 0.600），表明所提出的对应关系捕捉到了系统性的结构模式。性能表现因体裁（72.7%至89.9%）和角色（52.5%至99.2%）而异，定性分析显示这种差异反映了真实的叙事特性，包括传奇体裁中的功能分布规律以及讽刺体裁中有意识的原型颠覆。这种基于人物的研究方法展现了LLM支持的计算叙事学方法的潜力，并为未来叙事生成方法与交互式叙事应用的发展奠定了基础。