Drum Up SUPPORT: Systematic Analysis of Image-Schematic Conceptual Metaphors

Lennart Wachowiak, Dagmar Gromann, Chao Xu
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引用次数: 2

Abstract

Conceptual metaphors represent a cognitive mechanism to transfer knowledge structures from one onto another domain. Image-schematic conceptual metaphors (ISCMs) specialize on transferring sensorimotor experiences to abstract domains. Natural language is believed to provide evidence of such metaphors. However, approaches to verify this hypothesis largely rely on top-down methods, gathering examples by way of introspection, or on manual corpus analyses. In order to contribute towards a method that is systematic and can be replicated, we propose to bring together existing processing steps in a pipeline to detect ISCMs, exemplified for the image schema SUPPORT in the COVID-19 domain. This pipeline consist of neural metaphor detection, dependency parsing to uncover construction patterns, clustering, and BERT-based frame annotation of dependent constructions to analyse ISCMs.
唤起支持:意象图式概念隐喻的系统分析
概念隐喻是一种将知识结构从一个领域转移到另一个领域的认知机制。意象图式概念隐喻专门用于将感觉运动经验转移到抽象领域。自然语言被认为为这种隐喻提供了证据。然而,验证这一假设的方法主要依赖于自顶向下的方法,通过自省的方式收集示例,或手动语料库分析。为了建立一种系统且可复制的方法,我们建议将现有的处理步骤整合到一个流水线中,以检测iscm,例如COVID-19领域的图像模式支持。该管道由神经隐喻检测、依赖句法分析(揭示构造模式)、聚类和基于bert的依赖句法框架注释(分析iscm)组成。
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