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DL Meet FL: A Bidirectional Mapping between Ontologies and Linguistic Knowledge

机译:DL Meet FL:本体和语言知识之间的双向映射

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We present a transformation scheme that me-diates between description logics (DL) or RDF-encoded ontologies and type hierar-chies in feature logics (FL). The DL-to-FL direction is illustrated by an implemented offline procedure that maps ontologies with large, dynamically maintained instance data to named entity (NE) and information ex-traction (IE) resources encoded in typed fea-ture structures. The FL-to-DL translation is exemplified by a (currently manual) trans-lation of so-called MRS (Minimal Recur-sion Semantics) representations into OWL instances that are based on OWL classes, generated from the the type hierarchy of a deep linguistic grammar. The paper will identify parts of knowledge which can be translated from one formalism into the other without loosing information and parts which can only be approximated. The work de-scribed here is important for the Seman-tic Web to become a reality, since semantic annotations of natural language documents (DL) can be automatically generated by shal-low and deep natural language parsing sys-tems (FL).
机译:我们提出了一种转换方案,该转换方案介于描述逻辑(DL)或RDF编码的本体与特征逻辑(FL)中的类型层次结构之间。 DL到FL的方向由一个已实现的脱机过程来说明,该过程将具有大型动态维护实例数据的本体映射到以类型化特征结构编码的命名实体(NE)和信息提取(IE)资源。 FL到DL的翻译以(目前为手动)将所谓的MRS(最小递归语义)表示转换为基于OWL类的OWL实例为例,该OWL类是从深度类型的层次结构生成的语言语法。本文将确定可以从一种形式主义转化为另一种形式主义而又不丢失信息的知识部分和仅可以近似的部分。由于自然语言文档(DL)的语义注释可以通过深浅的自然语言解析系统(FL)自动生成,因此此处描述的工作对于实现语义网非常重要。

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