Paper: A Robust Risk Minimization Based Named Entity Recognition System

ACL ID W03-0434
Title A Robust Risk Minimization Based Named Entity Recognition System
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2003
Authors

This paper describes a robust linear classifica- tion system for Named Entity Recognition. A similar system has been applied to the CoNLL text chunking shared task with state of the art performance. By using different linguistic fea- tures, we can easily adapt this system to other token-based linguistic tagging problems. The main focus of the current paper is to investigate the impact of various local linguistic features for named entity recognition on the CoNLL- 2003 (Tjong Kim Sang and De Meulder, 2003) shared task data. We show that the system per- formance can be enhanced significantly with some relative simple token-based features that are available for many languages. Although more sophisticated linguistic features will also be helpful, they provide much less improve- ment than might...