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arXiv Computation and Language By Zheng Kui Lin

NS-ST-GraphRAG: Neuro-Symbolic Spatio-Temporal GraphRAG for Literary Knowledge Processing

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NS-ST-GraphRAG is a neuro‑symbolic spatio‑temporal GraphRAG framework designed to process long‑form literary narratives by integrating ontology‑guided extraction, deterministic constraint checking, dual temporal coordinates, spatial scene attributes, and dynamic sub‑graph retrieval. It selects the appropriate graph state based on the temporal and spatial scope of a query, grounding generated answers in traceable evidence. The authors also introduce Red‑Chamber‑QA, an open multi‑hop question‑answering benchmark for classical Chinese literature, and report that NS‑ST‑GraphRAG outperforms a frozen‑window baseline and a closed‑book model on a held‑out 120‑question split.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computation and Language.

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