A Named Entity Recognition Method using Rules Acquired from Unlabeled Data
Tomoya Iwakura · 2011
We propose a Named Entity (NE) recognition method using rules acquired from unlabeled data. Rules are acquired from automatically labeled data with an NE recognizer. These rules are used to identify NEs, the beginning of NEs, or the end of NEs. The application results of rules are used as features for machine learning based NE recognizers. In addition, we use word information acquired from unlabeled data as in a previous work. The word information includes the candidate NE classes of each word, the candidate NE classes of co-occurring words of each word, and so on. We evaluate our method with IREX data set for Japanese NE recognition and unlabeled data consisting of more than one billion words. The experimental results show that our method using rules and word information achieves the best accuracy on the GENERAL and ARREST tasks of IREX. 1