Japanese Named Entity Recognition Using Structural Natural Language Processing
Japanese Named Entity Recognition Using Structural Natural Language Processing
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发表时间：
2008
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通讯作者：
Ryohei Sasano;S. Kurohashi
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作者：
Ryohei Sasano;S. Kurohashi
提出了一种利用结构信息进行日语命名实体识别的方法。我们的NER系统是基于支持向量机（SVM），并利用四种类型的结构信息：缓存功能，共指关系，句法功能和案例框架功能，这是从结构分析。我们评估了我们的方法CRL NE数据，并获得了更高的F-措施比现有的方法，不使用结构信息。我们还进行了实验，IREX NE数据和NE标注的Web语料库，并证实，结构信息提高NER的性能。
This paper presents an approach that uses structural information for Japanese named entity recognition (NER). Our NER system is based on Support Vector Machine (SVM), and utilizes four types of structural information: cache features, coreference relations, syntactic features and caseframe features, which are obtained from structural analyses. We evaluated our approach on CRL NE data and obtained a higher F-measure than existing approaches that do not use structural information. We also conducted experiments on IREX NE data and an NE-annotated web corpus and confirmed that structural information improves the performance of NER.