Research on Improved TBL Based Japanese NER Post-Processing

摘要

An Improved TBL based post-processing approach is proposed for Japanese named entity recognition (NER) in this paper. Firstly, tuning rules are automatically acquired from the results of Japanese NER by error-driven learning. And then, the tuning rules are optimized according to given threshold conditions. After filtered, the rules are used to revise the results of Japanese NER. Above all, this approach could be used in special domains perfectly for its learning domain linguistic knowledge automatically. The learnt rules could not go over fit as well. The experimental results show that a high result can be achieved in precision for Japanese NER.