Design and Field Validation of a VR-Based RAG Historical NPC: Knowledge Grounding and Persona Grounding Can Fail Independently

Large language model (LLM)-based non-player characters (NPCs) can support unscripted historical dialogue, but their behavior in deployed educational virtual reality (VR) settings remains underexamined. This study reports the design and field validation of a self-hosted VR platform in which a retrieval-augmented generation (RAG) NPC, representing King Sejong the Great, engaged 42 international participants across 126 intercultural-learning sessions. The analytic corpus, reconstructed from retained session logs, comprised 104 sessions from 39 participants (2053 participant turns; 2053 NPC responses). Repetitive NPC response loops occurred in 33 sessions (31.7%), spanning 54 episodes and 190 responses, and co-occurred with learner-side transcript repetition in 31 of these sessions. The NPC maintained its first-person persona throughout the screened corpus, yet produced 30 biographical claims unsupported by the historical record: persona consistency did not ensure factual grounding. Prompt compliance varied by instruction type, and a post hoc implementation audit could not confirm that retrieved content contributed to individual responses. Together, these results identify persona grounding, knowledge grounding, retrieval observability, and session-level instrumentation as validation targets that deployed VR–LLM systems must address separately.