Single Character Chinese Named Entity Recognition

Single character named entity (SCNE) is a name entity (NE) composed of one Chinese character, such as “ ” (zhong1, China) and “ ” e2,Russia . SCNE is very common in written Chinese text. However, due to the lack of in-depth research, SCNE is a major source of errors in named entity recognition (NER). This paper formulates the SCNE recognition within the sourcechannel model framework. Our experiments show very encouraging results: an Fscore of 81.01% for single character location name recognition, and an F-score of 68.02% for single character person name recognition. An alternative view of the SCNE recognition problem is to formulate it as a classification task. We construct two classifiers based on maximum entropy model (ME) and vector space model (VSM), respectively. We compare all proposed approaches, showing that the sourcechannel model performs the best in most cases.