Revision of morphological analysis errors through the person name construction model

Abstract

In this paper, we present the method to automatically revise morphological analysis errors caused by unregistered person names. In order to detect and revise their errors, we propose the Person Name Construction Model for kanji characters composing Japanese names. Our method has the advantage of not using context information, like a suffix, to recognize person names, thus making our method a useful one. Through the experiment, we show that our proposed model is effective.