Paper: Chinese Named Entity Recognition With Multiple Features

ACL ID H05-1054
Title Chinese Named Entity Recognition With Multiple Features
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2005

This paper proposes a hybrid Chinese named entity recognition model based on multiple features. It differentiates from most of the previous approaches mainly as follows. Firstly, the proposed Hybrid Model integrates coarse particle feature (POS Model) with fine particle feature (Word Model), so that it can overcome the disadvantages of each other. Secondly, in order to reduce the searching space and improve the efficiency, we introduce heu- ristic human knowledge into statistical model, which could increase the perform- ance of NER significantly. Thirdly, we use three sub-models to respectively de- scribe three kinds of transliterated person name, that is, Japanese, Russian and Euramerican person name, which can im- prove the performance of PN recognition. From the experimental results on ...