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Automatic Animacy Classification

机译:自动动画分类

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摘要

We introduce the automatic annotation of noun phrases in parsed sentences with tags from a fine-grained semantic animacy hierarchy. This information is of interest within lexical semantics and has potential value as a feature in several NLP tasks. We train a discriminative classifier on an annotated corpus of spoken English, with features capturing each noun phrase's constituent words, its internal structure, and its syntactic relations with other key words in the sentence. Only the first two of these three feature sets have a substantial impact on performance, but the resulting model is able to fairly accurately classify new data from that corpus, and shows promise for binary animacy classification and for use on automatically parsed text.
机译:我们使用来自细粒度语义动画层次结构的标签介绍了已解析句子中名词短语的自动注释。此信息在词法语义中是令人感兴趣的,并且在某些NLP任务中具有潜在的功能。我们在带注释的英语口语语料库上训练判别式分类器,其特征是捕获每个名词短语的构成词,其内部结构以及与句子中其他关键词的句法关系。这三个功能集中只有前两个对性能有实质性影响,但是生成的模型能够相当准确地对来自该语料库的新数据进行分类,并显示出对二进制动画分类以及在自动解析文本中使用的希望。

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