Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics 2023
DOI: 10.18653/v1/2023.eacl-main.114
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FrameBERT: Conceptual Metaphor Detection with Frame Embedding Learning

Yucheng Li,
Shun Wang,
Chenghua Lin
et al.

Abstract: In this paper, we propose FrameBERT, a RoBERTa-based model that can explicitly learn and incorporate FrameNet Embeddings for concept-level metaphor detection. FrameBERT not only achieves better or comparable performance to the state-of-the-art, but also is more explainable and interpretable compared to existing models, attributing to its ability of accounting for external knowledge of FrameNet.

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