Researchers proposed a two-stage framework to automate the construction of a business semantic layer from raw application logs using a hierarchical Large Language Model (LLM) and Retrieval-Augmented Generation (RAG). This approach improves semantic quality, reduces maintenance effort, and filters out noise, enabling continuous quality assurance.