Paper: A Framework Based on Graphical Models with Logic for Chinese Named Entity Recognition

ACL ID I08-1044
Title A Framework Based on Graphical Models with Logic for Chinese Named Entity Recognition
Venue International Joint Conference on Natural Language Processing
Session Main Conference
Year 2008
Authors

Chinese named entity recognition (NER) has re- cently been viewed as a classification or sequence labeling problem, and many approaches have been proposed. However, they tend to address this problem without considering linguistic informa- tioninChineseNEs. Weproposeanewframework based on probabilistic graphical models with first- order logic for Chinese NER. First, we use Condi- tional Random Fields (CRFs), a standard and the- oretically well-founded machine learning method based on undirected graphical models as a base system. Second, we introduce various types of domain knowledge into Markov Logic Networks (MLNs), an effective combination of first-order logic and probabilistic graphical models for vali- dation and error correction of entities. Experimen- tal results show that our framewo...