FrameBERT: Conceptual Metaphor Detection with Frame Embedding Learning
About
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.
Yucheng Li, Shun Wang, Chenghua Lin, Frank Guerin, Lo\"ic Barrault• 2023
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Metaphor Detection | MOH-X | F1 Score78 | 15 | |
| Metaphor Detection | TroFi | F1 Score62 | 15 | |
| Metaphor Prediction | VUA 18 | Accuracy93.3 | 6 | |
| Metaphor Prediction | VUA-18 (test) | Binary F176.6 | 6 |
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