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Class-Driven Attribute Extraction

机译:类驱动的属性提取

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摘要

We report on the large-scale acquisition of class attributes with and without the use of lists of representative instances, as well as the discovery of unary attributes, such as typically expressed in English through prenominal adjectival modification. Our method employs a system based on compositional language processing, as applied to the British National Corpus. Experimental results suggest that document-based, open class attribute extraction can produce results of comparable quality as those obtained using web query logs, indicating the utility of exploiting explicit occurrences of class labels in text.
机译:我们报告了在有或没有使用代表实例列表的情况下大规模获取类属性的情况,以及一元属性的发现,例如通常通过名词修饰语用英语表示的一元属性。我们的方法采用了基于构成语言处理的系统,该系统已应用于不列颠国家语料库。实验结果表明,基于文档的开放类属性提取可以产生与使用Web查询日志获得的结果相当的质量,这表明利用文本中显式出现的类标签是有用的。

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