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Automatic compilation of language resources for named entity recognition in Turkish by utilizing Wikipedia article titles

机译:利用维基百科文章标题自动编译语言资源,以土耳其语命名实体识别

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摘要

We present an automatic approach to compile language resources for named entity recognition (NER) in Turkish by utilizing Wikipedia article titles. First, a subset of the article titles is annotated with the basic named entity types. This subset is then utilized as training data to automatically classify the remaining titles by employing the k-nearest neighbor algorithm, leading to the construction of a significant lexical resource set for Turkish NER. Experiments on different text genres are conducted after extending an existing NER system with the resources and the results obtained confirm that the resources contribute to NER on different genres.
机译:通过使用维基百科的文章标题,我们提出了一种自动方法来为土耳其的命名实体识别(NER)编译语言资源。首先,用基本的命名实体类型注释文章标题的子集。然后将该子集用作训练数据,以通过使用k最近邻算法自动对其余标题进行分类,从而为土耳其语NER构造重要的词汇资源集。在利用资源扩展了现有的NER系统后,对不同的文本类型进行了实验,获得的结果证实了资源对不同类型的NER都有贡献。

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