Inproceedings,
»Japan’s Answer to Mozart«: Automatic Detection of Generalized Patterns of Vossian Antonomasia
Proceedings of the 6th International Conference on Natural Language and Speech Processing, Association for Computational Linguistics, (2023)
Abstract
Vossian Antonomasia (VA) is a rhetorical device used to describe an entity (the target) by transferring certain features and characteristics of another entity (the source) to it. The phenomenon is closely related to metaphor and metonymy. Similar to these more familiar devices, the detection of VA expressions is a challenging task. We propose novel VA detection models that center on the source to tackle this problem. The focus lies on the ability of the models to detect VA independent of the syntactic patterns they appear in. We model the problem in different scenarios and utilize a state-of-the-art metonymy resolution model that relies on word masking, and metaphor detection models, which are based on linguistic metaphor theories, and adjust them to our task. All models leverage pre-trained language models such as BERT and RoBERTa. As there is limited annotated data available, we use a data augmentation technique to create a new dataset consisting of VA with new syntactic patterns where the generalization ability of the models can be evaluated.
