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Semantic Enriching of Natural Language Texts with Automatic Thematic Role Annotation

机译:具有自动主题角色注释的自然语言文本的语义富集

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This paper proposes an approach which utilizes natural language processing (NLP) and ontology knowledge to automatically denote the implicit semantics of textual requirements. Requirements documents include the syntax of natural language but not the semantics. Semantics are usually interpreted by the human user. In earlier work Gelhausen and Tichy showed that SALEMX automatically creates UML domain models from (semantically) annotated textual specifications [1]. This manual annotation process is very time consuming and can only be carried out by annotation experts, We automate semantic annotation so that SALEMX can be completely automated. With our approach, the analyst receives the domain model of a requirements specification in a very fast and easy manner. Using these concepts is the first step into farther automation of requirements engineering and software development.
机译:本文提出了一种利用自然语言处理(NLP)和本体知识来自动表示文本要求的隐式语义的方法。要求文档包括自然语言的语法,但不是语义。语义通常由人类用户解释。在早期的工作中,Gelhausen和Tichy显示Salemx自动从(语义上)注释的文本规范[1]自动创建UML域模型。本手册注释过程非常耗时,只能通过注释专家进行,我们自动化语义注释,以便Salemx可以完全自动化。通过我们的方法,分析师以非常快速和简单的方式接收需求规范的域模型。使用这些概念是进入需求工程和软件开发的进一步自动化的第一步。

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