Improving the Scalability of Semi-Markov Conditional Random Fields for Named Entity Recognition

This paper presents techniques to apply semi-CRFs to Named Entity Recognition tasks with a tractable computational cost. Our framework can handle an NER task that has long named entities and many labels which increase the computational cost. To reduce the computational cost, we propose two techniques: the first is the use of feature forests, which enables us to pack feature-equivalent states, and the sec

• Type: Conference
• Year: 2006
• Where: ACL
• Authors: Daisuke Okanohara, Yusuke Miyao, Yoshimasa Tsuruoka, Jun-ichi Tsujii
• Keywords: ACL 2006, ACL 2007, Computational Cost, Named Entity Recognition, Tractable Computational Cost