In this paper, we propose an innovative approach to model narratives, especially movie plots and other narrative content, through the integration of semantic analysis and storytelling structure. Using the principles of storytelling, we systematically decompose the stories that are the subject of movie or book plots into their fundamental rhetorical components, such as the various actions, the relationships between events, the characters involved, and the underlying themes. Our method employs logical inference rules to identify recurrent narrative structures, facilitating the extraction of patterns that can be observed in different stories and movies. This approach not only improves the understanding of narrative construction, but also provides a framework for the automatic analysis and comparison of different narrative forms. To demonstrate the effectiveness of the methodology, we tested it on the case study of the filmography of the Marvel Universe, as it provides examples of movies whose plot is very complex and the movies together form a network of connections, and being a well-known domain, it facilitates our understanding of the example. Our results demonstrate the effectiveness of this model in revealing common structural elements in a variety of narrative datasets, highlighting its potential applications in fields such as literary analysis, screenwriting, and AI-driven content generation.