Rockstroh, JohannaJohannaRockstrohD'Ippolito, GiadaGiadaD'IppolitoLazzari, NicolasNicolasLazzariOudshoorn, Anouk M.Anouk M.OudshoornPurohit, DishaDishaPurohitRaoufi, EnsiyehEnsiyehRaoufiRudolph, SebastianSebastianRudolph2025-08-222025-08-222023https://media.suub.uni-bremen.de/handle/elib/22267https://doi.org/10.26092/elib/4230A Vossian Antonomasia (VA) is a stylistic device used to describe a person (or, more generally, an entity) in terms of a well-known person and a modifying context. For instance, the Norwegian chess world champion Magnus Carlsen was described as “the Mozart of chess” [1]. All VAs follow the pattern where a source (e.g., “Mozart”), is used to describe a target, (e.g., “Magnus Carlsen”), and the transfer of meaning is “channeled” through the use of the modifier “of chess”. Although this rhetorical figure is well-known, there has not yet been a dedicated study of targeted automatic or semi-automatic methods to generate and judge the appropriateness of VAs using large Knowledge Graphs (KGs) such as Wikidata. In our work, we propose the use of vector space embeddings – both KG-based and text-based – for producing VAs. For comparison, we contrast our findings with a purely LLM-based approach, wherein VAs are obtained from ChatGPT using a reasonably engineered prompt. We provide a publicly available GitHub repository1 for the implementation of our method and a website that allows testing the proposed methods.15enhttps://creativecommons.org/licenses/by/4.0/Vossian Antonomasias (VA)personentityKnowledge GraphsWikidatavector space embeddings000 Informatik, Informationswissenschaft, allgemeine Werke::000 Informatik, Wissen, SystemeText::Konferenzveröffentlichung::Tagungsband::Konferenzbeitrag10.26092/elib/4230urn:nbn:de:gbv:46-elib222671