In this work, we propose a hybrid approach for legal norm retrieval that combines the structural information modeled in knowledge graphs with the textual content of legal documents. Our method utilizes the intricate relationships within the Japanese Civil Code, supplemented by relevant precedents, references, commentary, and mentions in legal textbooks on Japanese law. We assess the effectiveness of our approach in Task 3 of the Competition on Legal Information Extraction/Entailment (COLIEE), using both a transformer model and BM25 as a more explainable retrieval model. In our experiments, we examine the contributions of the different legal document types, showing the positive impact of the knowledge graph and auxiliary information.