In this paper we propose a named entity recognizer (NER) which we can train from partially annotated data. As the natural language processing is getting to be applied to diverse texts, there arise high demands for the NER for new named entity (NE) definition in different domains. For these special NE definitions, only a small annotated corpus is available in the beginning, and a rapid and low-c...
