An approach for Chinese named entity identification using cascaded hidden Markov model

which aimed to incorporate person name

location name

organization name recognition into an integrated theoretical frame was presented.Simple named entity was recognized by lower HMM model after rough segmentation and complex named entity such as person name

location name and organization name was recognized by higher HMM model using role tagging.In the test on large realistic corpus

its F-1 measure of person name

location name and organization name was 92.55%

94.53% and 86.51%.In the first international word segmentation bakeoff held by SIGHAN（the ACL Special Interest Group on Chinese Language Processing） in 2003.ICTCLAS

which name entity identification base on this model achieved excellent score.