A is the B of C: (Semi)-Automatic Creation of Vossian Antonomasias

Giada D’Ippolito, Nicolas Lazzari, Anouk Michelle Oudshoorn, Disha Purohit, Ensiyeh Raoufi, Johanna Rockstroh, Sebastian Rudolph

TL;DR: In our paper, we propose employing knowledge graph and word embeddings for generating Vossian Antonomasia (VA), and then compare these methods with a ChatGPT-based approach by conducting a user study to gauge their effectiveness and appropriateness.

Abstract:

A 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”. 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 website2 that allows testing the proposed methods.

Submission Number: 7