We propose a taxonomy-guided approach to semantic alignment that assigns lexicographic senses to an onomasiological taxonomy derived from the Hallig–Wartburg/Post system. Using an LLM under strict taxonomic constraints, short and heterogeneous meaning descriptions are assigned to a common conceptual space. Evaluation against expert annotation shows that run-to-run model agreement (kappa = 0.73) closely matches human agreement (kappa = 0.74), with robustness at coarse taxonomic levels and predictable degradation at finer granularity. A qualitative network analysis demonstrates the resulting potential for cross-dictionary exploration of dialectal variation in semantics.

This paper applies the ontology-baseddialectometric technique of Engsterhold(2020) to surnames. The method wasoriginally developed for phonetic analyses. However, as will be shown, it is also suitedfor the study of graphemic representations. Based on data from the German SurnameAtlas (DFA), the method is optimized forgraphemic analysis and illustrated with anexample case.