Abstract: This paper carried out a series of experiments on Chinese relation extraction classification based on standard and training corpus of ACE2005 (Automatic Content Extraction 2005) . It explores word, entity, syntax, gram features in Chinese at first, and then present a method which combines these basic features. The F-score of Chinese relation extraction for Relation Detection and six major types in ACE2005 Chinese corpora improves 1.36% and 3.97% and achieves 72.77 and 61.03 respectively in SVM, then give the contribution of different combined features. It illustrates that the combined features of words and entities are very effective for Chinese Relation Extraction.