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A Graph Grammar Approach to Map between Dependency Trees and Topological Models

机译:依赖树木与拓扑模型映射的图语法方法

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Determining the word order in free word order languages is deemed as a challenge for NLG. In this paper, we propose a simple approach in order to get the appropriate grammatically correct variants of a sentence using a dependency structure as input. We describe a linearization grammar based on a graph grammar that allows to retrieve a topological model using unordered constituent structures and precedence relations. The graph grammar formalism is totally language independent and only the grammar depends on the language. The grammar rules can be automatically acquired from a corpus that is annotated with phrase structures and dependency structures. The dependency structures annotation is retrieved by structure translation from the phrase structure annotation. We conclude with the description of a grammar and the evaluation of the formalism using a large corpus.
机译:以免费的单词顺序语言确定单词顺序被视为NLG的挑战。 在本文中,我们提出了一种简单的方法,以便使用依赖结构作为输入获得句子的适当语法正确变体。 我们基于图形语法描述了一个线性化语法,允许使用无序的构成结构和优先关系来检索拓扑模型。 图语法形式主义是完全的语言独立,只有语法取决于语言。 语法规则可以从用短语结构和依赖结构注释的语料库自动获取。 通过与短语结构注释的结构转换检索依赖性结构注释。 我们在使用语法的描述和使用大型语料库的形式主义的评估结束。

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