Abstract

Commonsense knowledge is a broad and challenging area of research which investigates our understanding of the world as well as human assumptions about reality. Deriving directly from the subjective perception of the external world, it is intrinsically intertwined with embodied cognition. Commonsense reasoning is linked to human sense-making, pattern recognition and knowledge framing abilities. This work presents a new resource that formalizes the cognitive theory of image schemas. Image schemas are dynamic conceptual building blocks originating from our sensorimotor interactions with the physical world, and enable our sense-making cognitive activity to assign coherence and structure to entities, events and situations we experience everyday. ImageSchemaNet is an ontology that aligns pre-existing resources, such as FrameNet, VerbNet, WordNet and MetaNet from the Framester hub, to image schema theory. This article describes an empirical application of ImageSchemaNet, combined with semantic parsers, on the task of annotating natural language sentences with image schemas.

中文翻译：

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ImageSchemaNet：体现常识知识的框架图

摘要

常识知识是一个广泛且具有挑战性的研究领域，它调查我们对世界的理解以及人类对现实的假设。它直接源自对外部世界的主观感知，本质上与具体认知交织在一起。常识推理与人类的意义建构、模式识别和知识构建能力相关。这项工作提供了一种新的资源，将图像图式的认知理论形式化。图像图式是源自我们与物理世界的感觉运动相互作用的动态概念构建块，使我们的意义认知活动能够为我们每天经历的实体、事件和情况分配连贯性和结构。ImageSchemaNet 是一种本体论，它将现有资源（例如来自 Framester 中心的 FrameNet、VerbNet、WordNet 和 MetaNet）与图像模式理论结合起来。本文描述了 ImageSchemaNet 与语义解析器相结合，在用图像模式注释自然语言句子的任务中的实证应用。