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Classification-Based Filtering of Semantic Relatedness in Hypernymy Extraction

机译:基于分类的语义提取中的语义相关性过滤

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Manual construction of a wordnet can be facilitated by a system that suggests semantic relations acquired from corpora. Such systems tend to produce many wrong suggestions. We propose a method of filtering a raw list of noun pairs potentially linked by hypernymy, and test it on Polish. The method aims for good recall and sufficient precision. The classifiers work with complex features that give clues on the relation between the nouns. We apply a corpus-based measure of semantic relatedness enhanced with a Rank Weight Function. The evaluation is based on the data in Polish WordNet. The results compare favourably with similar methods applied to English, despite the small size of Polish WordNet.
机译:可以通过建议从语料库中获取语义关系的系统来方便手动构建词网。这样的系统往往会产生许多错误的建议。我们提出了一种过滤可能由上位词链接的名词对的原始列表的方法,并在波兰语上对其进行了测试。该方法旨在实现良好的召回率和足够的精度。分类器具有复杂的功能,可提供有关名词之间关系的线索。我们应用了基于语料库的语义相关性度量,并通过秩权重函数进行了增强。评估基于波兰WordNet中的数据。尽管波兰语WordNet的规模很小,但结果与采用英语的类似方法相比还是令人满意的。

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