FrameBERT:基于框架嵌入学习的概念隐喻检测
FrameBERT: Conceptual Metaphor Detection with Frame Embedding Learning
摘要:
在本文中,我们提出了FrameBERT,一个基于RoberTa的模型,可以显式地学习和纳入框架网络嵌入概念级隐喻检测。FrameBERT不仅实现了更好的或与最先进的性能相当的性能,而且与现有模型相比,它具有更好的解释性和可解释性,这归因于它能够解释FrameNet的外部知识。
英文摘要:
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.
机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。