Intelligent Construction of LVC Resource Interface Protocol Templates Using Large Language Models

The construction of resource interface protocol templates is a key prerequisite for the unified integration of live, virtual, and constructive (LVC) resources in complex simulation and test environments. However, real-world protocol documents are usually heterogeneous in format, inconsistent in description, and rich in nested structures and implicit semantics, which makes manual analysis inefficient and error-prone. To address this issue, this paper proposes an intelligent construction method for LVC resource interface protocol templates based on large language models. First, raw protocol documents are converted into a unified Markdown representation, and a semantic understanding module is used for main-table identification, minimum-unit splitting, and auxiliary-table association. Then, a protocol item type identification expert module is designed to recognize complex structures such as frame headers, ordinary items, dynamic items, struct items, branch items, sub-protocol items, and checksum items. Finally, the extracted information is integrated into structured intermediate results for automatic XML template generation. Experiments on a representative test set composed of 20 protocol tables from real-world LVC resource interface documents show that the proposed method achieves a main-table extraction accuracy of 0.9761, a type recognition F1-score of 0.9769, an XML generation success rate of 1.0, and a node consistency of 0.9478. These results demonstrate that the proposed method can effectively improve the automation and engineering applicability of protocol template construction.