Narrative-to-Scene Generation: An LLM-Driven Pipeline for 2D Game Environments

• URL: http://arxiv.org/abs/2509.04481v1
• Date: Sun, 31 Aug 2025 01:45:56 GMT
• Title: Narrative-to-Scene Generation: An LLM-Driven Pipeline for 2D Game Environments
• Authors: Yi-Chun Chen, Arnav Jhala,
• Abstract summary: We present a lightweight pipeline that transforms short narrative prompts into a sequence of 2D tile-based game scenes.<n>Given an LLM-generated narrative, our system identifies three key time frames, extracts spatial predicates, and retrieves visual assets.<n>A layered terrain is generated using Cellular Automata, and objects are placed using spatial rules grounded in the predicate structure.
• Score: 0.09821874476902966
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: Recent advances in large language models(LLMs) enable compelling story generation, but connecting narrative text to playable visual environments remains an open challenge in procedural content generation(PCG). We present a lightweight pipeline that transforms short narrative prompts into a sequence of 2D tile-based game scenes, reflecting the temporal structure of stories. Given an LLM-generated narrative, our system identifies three key time frames, extracts spatial predicates in the form of "Object-Relation-Object" triples, and retrieves visual assets using affordance-aware semantic embeddings from the GameTileNet dataset. A layered terrain is generated using Cellular Automata, and objects are placed using spatial rules grounded in the predicate structure. We evaluated our system in ten diverse stories, analyzing tile-object matching, affordance-layer alignment, and spatial constraint satisfaction across frames. This prototype offers a scalable approach to narrative-driven scene generation and lays the foundation for future work on multi-frame continuity, symbolic tracking, and multi-agent coordination in story-centered PCG.

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