Using decision trees to select the grammatical relation of a noun phrase

Simon Corston-Oliver
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引用次数: 4

Abstract

We present a machine-learning approach to modeling the distribution of noun phrases (NPs) within clauses with respect to a fine-grained taxonomy of grammatical relations. We demonstrate that a cluster of superficial linguistic features can function as a proxy for more abstract discourse features that are not observable using state-of-the-art natural language processing. The models constructed for actual texts can be used to select among alternative linguistic expressions of the same propositional content when generating discourse.
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用决策树选择名词短语的语法关系
我们提出了一种机器学习方法,根据语法关系的细粒度分类法对子句内名词短语(NPs)的分布进行建模。我们证明了一组肤浅的语言特征可以作为更抽象的话语特征的代理,这些特征是使用最先进的自然语言处理无法观察到的。为实际文本构建的模型可用于在生成语篇时对相同命题内容的替代语言表达进行选择。
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