论文信息 - Chinese Word Segmentation and Named Entity Recognition Based on Conditional Random Fields Models

Chinese Word Segmentation and Named Entity Recognition Based on Conditional Random Fields Models

This paper mainly describes a Chinese named entity recognition (NER) system NER@ISCAS, which integrates text, part-of-speech and a small-vocabularycharacter-lists feature for MSRA NER open track under the framework of Conditional Random Fields (CRFs) model. The techniques used for the close NER and word segmentation tracks are also presented.

Le Sun | Yuanhua Lv | Yuanyong Feng

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[2] Le Sun,et al. Early results for Chinese named entity recognition using conditional random fields model, HMM and maximum entropy , 2005, 2005 International Conference on Natural Language Processing and Knowledge Engineering.