This manual focuses on the initial phase of a (digital) publishing process. It offers methods to critically examine the narrative structures of content and explore alternative conceptions of a publication. By raising the question of how modular publishing can be used as a way to create, edit and structure content it tries to resist a monolithic story line, and embraces multiple perspectives.
In this paper we introduce a novel highly interactive process to generate natural language narratives on the basis of our ongoing work on semiotic relations. To the two basic components of interactive systems, namely, a software tool and a user interface, we add a third component - AI agents, understood as an upgraded rendition of software agents. Our semiotic relations approach considers four ways of composing new narratives from existing narratives. Along what semioticians call the horizontal syntagmatic axis, one can form the new narrative by combining two or more previous narratives. Along the vertical paradigmatic axis, the new narrative may emerge as a similar version, which imitates the previous one, possibly in a different context. Along the depth meronymic axis, the hierarchic narrative levels, such as plot, event, and scene, are explored, allowing either expansion or summarization. Lastly, the antithetic consideration, rather than adding a dimension, aims at some form of reversal, through the adoption of opposite values. A fully operational prototype is described. Its name, ChatGeppetto, conflates the skilled Geppetto, who fashioned Pinocchio, an early case of artisanship-produced human level intelligence, with ChatGPT, which operates as the main AI agent component. To run the experiments, we concentrated on book narratives.
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This article presents a novel and highly interactive process to generate natural language narratives based on our ongoing work on semiotic relations, providing four criteria for composing new narratives from existing stories. The wide applicability of this semiotic reconstruction process is suggested by a reputed literary scholar's deconstructive claim that new narratives can often be shown to be a tissue of previous narratives. Along, respectively, three semiotic axes – syntagmatic, paradigmatic, and meronymic – existing stories can yield new stories by the combination, imitation, or expansion of an iconic scene; lastly, a new story may emerge through reversal via an antithetic consideration, i.e., through the adoption of opposite values. Targeting casual users, we present a fully operational prototype with a simple and user-friendly interface that incorporates an AI agent, namely ChatGPT. The prototype, in a coauthor capacity, generates context-compatible sequences of events in storyboard format using backward-chaining abductive reasoning (employing Stable Diffusion to draw scene illustrations), conforming as much as possible to the user's authorial instructions. The extensive repertoire of book and movie summaries available to the AI agent obviates the need to manually supply laborious and error-prone context specifications. A user study was conducted to evaluate user experience and satisfaction with the generated narratives. The preliminary findings suggest that our approach has the potential to enhance story quality while offering a positive user experience.
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