While generative artificial intelligence is being fully integrated into architectural heritage narratives and design applications, the structured representation of Lingnan architectural culture knowledge remains lacking. This paper selects the Xiguan historical district in Guangzhou and the Ancestral Temple-Lingnan Tiandi area in Foshan as research areas, creating a multi-source corpus integrating local chronicles, planning texts, field investigations, and oral histories. An ontological framework of "time period—building type— component — craft—imagery" is presented, and unified semantic embedding is obtained through domain pre-training and graph representation. Based on this, a generative architecture integrating retrieval enhancement and lightweight fine-tuning is formed, and evaluation is conducted for three types of tasks: knowledge question answering, architectural description, and design assistance. The results show that this corpus significantly improves the recall rate of cultural entities and the consistency of Lingnan style, and also outperforms general models in terms of design efficiency and text quality, providing technical support for the digital inheritance and intelligent generation of regional architectural culture.

Linhong Li, Min Wang. Construction and Application of Lingnan Architectural Culture Corpus under the Background of Generative Artificial Intelligence. The Frontiers of Society, Science and Technology (2025), Vol. 7, Issue 8: 49-57. https://doi.org/10.25236/FSST.2025.070808.

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