ME-BASED CHINESE PERSON NAME AND LOCATION NAME RECOGNITION MODEL

摘要

This paper constructs a hybrid model for automatic Chinese person name and location name recognition, which is based on Maximum Entropy principle.The model consists of a training module and a recognizing module.Firstly, contextual features are extracted from the training corpus.Maximum Entropy principle is employed to train the features.Then, the trained features together with a Dynamic Word List and a simple Rule Base are used to recognize Chinese person names and location names in the testing corpus.The experimental results are satisfying and have been analyzed.