Auditable analysis of corporate climate disclosures requires retrieving, for each regulatory disclosure requirement, the report page or section that contains the evidence. We study ontology-aware query expansion (OAE) for ESRS E1 (Climate Change) requirements over a new page/section-level benchmark: five companies, 1,177 real-artifact chunks, and 114 human-reviewed gold labels, plus a held-out ESRS-native company (64 labels) unseen during ontology construction. Against lexical, dense, hybrid, and pseudo-relevance-feedback (PRF) baselines, a lightweight ontology built from the standard’s requirements improves retrieval: the best configuration reaches Recall@10 0.842 vs. BM25’s 0.702 (McNemar p=.003). Generic PRF expansion hurts retrieval while ontology-guided expansion helps; a corpus-blind LLM query expander is a far stronger control and ties with the ontology in-domain, but does not transfer to the held-out company, where OAE stays ahead of lexical, dense, and LLM-expansion baselines while being statistically indistinguishable from cross-encoder reranking — a comparison we treat as diagnostic rather than conclusive. We provide an error analysis of the residual misses. “Gold” denotes retrieval ground truth only; we make no company scoring or compliance judgement.