Structural Blueprint Interpretation for Unsupervised Entity Understanding in Multi-Domain Text

This study proposes a blueprint-driven semantic interpretation framework that constructs high-level structural diagrams for textual content without any annotated labels. A blueprint generator synthesizes structural templates from syntactic patterns, and a constraint-matching engine aligns sentence components to blueprint slots. Tests on MixedNews-ZS, LegalText-ZS, and ScienceCorpus-ZS show improved structural consistency, with F1 gains of 11.7%, 13.4%, and 15.2% over syntax-only baselines. The model reduces role ambiguity errors by 26.9% and achieves a 19.8% improvement in zero-annotation entity function resolution. Cross-lingual experiments further demonstrate that blueprint mapping maintains 87.1% performance when transferring from English to German.