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This paper introduces the Narrative World Model (NWM), a memory system for long-form fiction writers that uses narratology-grounded typed temporal-state graphs and query-conditioned hybrid retrieval to answer multi-hop questions about evolving story state. The system significantly outperforms existing temporal-knowledge-graph frameworks like Graphiti on benchmark narratological QA tasks.