关键词: 隐马尔科夫模型, 特殊实体, 扩充词性, 动画自动生成

Abstract: Academician Lu Ruqian proposed Full Cycle Computer Aided Animation Auto-generation Technology based on artificial intelligence technology. The technology needs to recognize special types of named entities such as school names, restaurant names and emporium names, which can be performed in animation. A method for recognizing special types of named entities is proposed based on the Hidden Markov Model（HMM） and rules. The method uses HMM and trains the model with part-of-speech information, feature words and the sense of words, then complements and corrects the recognition results of HMM with rules automatically extracted from the training corpus and entity names. The accuracy, recall and F-score of the open testing experiment reaches 79.89%, 86.6% and 83.11%.

Key words: Hidden Markov Model（HMM）, special kinds of named entity, expanded part-of-speech, animation auto-generation