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Towards Data-Driven Style Checking: An Example for Law Texts

机译:迈向数据驱动的风格检查:法律文本的示例

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We present a novel approach to detecting syntactic structures that are inadequate for their domain context. We define writing style in terms of the choices between alternatives, and conducted an experiment in the legislative domain on the syntactic choice of nominalization in German, i.e. complex noun phrase vs. relative clause. In order to infer the stylistic choices that are conventional in the domain, we capture the contexts that affect the syntactic choice. Our results showed that a data-driven binary classifier can be a viable method for modelling syntactic choices in a style-checking tool.
机译:我们提出了一种检测域内背景不足的句法结构的新方法。我们在替代方案之间的选择方面定义了写作风格,并在德语中的名词化语法选择的立法领域进行了实验,即复杂的名词短语与相对条款。为了推断域中传统的风格选择,我们捕获影响句法选择的上下文。我们的结果表明,数据驱动的二进制分类器可以是用于在样式检查工具中建模句法选择的可行方法。

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