Publication | Open Access
FrameBERT: Conceptual Metaphor Detection with Frame Embedding Learning
20
Citations
25
References
2023
Year
Unknown Venue
EngineeringExternal KnowledgeSemanticsCorpus LinguisticsText MiningWord EmbeddingsApplied LinguisticsNatural Language ProcessingVisual GroundingComputational LinguisticsFramenet EmbeddingsLanguage StudiesMachine TranslationSemantic InterpretationVision Language ModelSymbolic Linguistic RepresentationConcept-level Metaphor DetectionVisual MetaphorFrame Embedding LearningLinguisticsSemantic Representation
In this paper, we propose FrameBERT, a BERT-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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