Paper: Japanese Named Entity Recognition Using Structural Natural Language Processing

ACL ID I08-2080
Title Japanese Named Entity Recognition Using Structural Natural Language Processing
Venue International Joint Conference on Natural Language Processing
Session Main Conference
Year 2008
Authors

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 informa- tion: 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 exist- ing approaches that do not use structural in- formation. We also conducted experiments on IREX NE data and an NE-annotated web corpus and confirmed that structural infor- mation improves the performance of NER.