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Linking Semantic and Knowledge Representations in a Multi-Domain Dialogue System

机译:在多域对话系统中链接语义和知识表示

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摘要

We describe a two-layer architecture for supporting semantic interpretation and domain reasoning in dialogue systems. Building system that supports both semantic interpretation and domain reasoning in a transparent and well-integrated manner is an unresolved problem because of the diverging requirements of the semantic representations used in contextual interpretation versus the knowledge representations used in domain reasoning. We propose an architecture that provides both portability and efficiency in natural language interpretation by maintaining separate semantic and domain knowledge representations, and integrating them via an ontology mapping procedure. The ontology mapping is used to obtain representations of utterances in a form most suitable for domain reasoners and to automatically specialize the lexicon. The use of a linguistically motivated parser for producing semantic representations for complex natural language sentences facilitates building portable semantic interpretation components as well as connections with domain reasoners. Two evaluations demonstrate the effectiveness of our approach: we show that a small number of mapping rules are sufficient for customizing the generic semantic representation to a new domain, and that our automatic lexicon specialization technique improves parser speed and accuracy.
机译:我们描述了一个两层体系结构,用于在对话系统中支持语义解释和域推理。由于上下文解释中使用的语义表示与领域推理中使用的知识表示的要求不同,以透明且集成良好的方式支持语义解释和领域推理的构建系统尚未解决。我们提出了一种体系结构,该体系结构通过维护单独的语义和领域知识表示并通过本体映射过程将它们集成在一起,从而在自然语言解释中同时提供可移植性和效率。本体映射用于以最适合域推理器的形式获取话语表示,并自动专门化词典。使用语言动机的解析器来生成复杂自然语言句子的语义表示,有助于构建可移植的语义解释组件以及与域推理器的连接。两次评估证明了我们方法的有效性:我们证明了少量映射规则足以将通用语义表示定制到一个新域,并且我们的自动词典专业化技术提高了解析器的速度和准确性。

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