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Build2SPARQL introduces a large-scale KG-grounded benchmark (6,136 validated SPARQL queries, 30,680 questions) for text-to-SPARQL querying over building knowledge graphs, where SPARQL queries are generated and validated by graph-traversal code and LLMs only produce natural-language questions. Retrieval-augmented evaluation of three open-weight models lifts exact-match accuracy from 0.2–20% zero-shot to 56–65% with three-shot retrieved context.
This paper presents FDD-ON, a modular ontology for representing VAV HVAC system components, faults, symptoms, and impacts to enable interoperable fault detection and diagnostics applications.