  Dialogue-based Role Playing Games (RPGs) require powerful storytelling. The
narratives of these may take years to write and typically involve a large
creative team. In this work, we demonstrate the potential of large generative
text models to assist this process. \textbf{GENEVA}, a prototype tool,
generates a rich narrative graph with branching and reconverging storylines
that match a high-level narrative description and constraints provided by the
designer. A large language model (LLM), GPT-4, is used to generate the
branching narrative and to render it in a graph format in a two-step process.
We illustrate the use of GENEVA in generating new branching narratives for four
well-known stories under different contextual constraints. This tool has the
potential to assist in game development, simulations, and other applications
with game-like properties.
