Paper: A Hybrid Approach To Biomedical Named Entity Recognition And Semantic Role Labeling

ACL ID N06-3009
Title A Hybrid Approach To Biomedical Named Entity Recognition And Semantic Role Labeling
Venue Human Language Technologies
Session Doctoral Consortium
Year 2006
Authors

In this paper, we describe our hybrid ap- proach to two key NLP technologies: biomedical named entity recognition (Bio-NER) and (Bio-SRL). In Bio-NER, our system successfully integrates linguis- tic features into the CRF framework. In addition, we employ web lexicons and template-based post-processing to further boost its performance. Through these broad linguistic features and the nature of CRF, our system outperforms state-of- the-art machine-learning-based systems, especially in the recognition of protein names (F=78.5%). In Bio-SRL, first, we construct a proposition bank on top of the popular biomedical GENIA treebank fol- lowing the PropBank annotation scheme. We only annotate the predicate-argument structures (PAS’s) of thirty frequently used biomedical verbs (predicates) and their...