In this paper, we address the problem of answering questions about preconditions in the law, e.g. “When can the court terminate the guardianship of a natural person?”. When answering legal questions, it is important to attribute the relevant part of the law; we therefore not only generate answers but also references to law articles. We implement a retrieval augmented generation (RAG) pipeline for long-form answers based on the Dutch law, using several state-of-the-art retrievers and generators. For evaluating our pipeline, we create a dataset containing legal QA pairs with attributions. Our experiments show promising results on our extended version for the automatic evaluation metrics from the Automatic LLMs’ Citation Evaluation (ALCE) Framework and the G-EVAL Framework. Our findings indicate that RAG has significant potential in complex, citation-heavy domains like law, as it helps laymen understand legal preconditions and rights by generating high-quality answers with accurate attributions.