Discovering and Counting Biomedical Verbs

In the biomedical domain verbs tend to be drawn from a smaller and more regular vocabulary than standard English and are especially informative for predicting the semantic class of the entities involved. With this motivation we investigate the discovery and counting of verbs in the biomedical domain by applying part-of-speech tagging and unsupervised morphological analysis. Our goal is to automatically discover an almost complete set of relevant verbs and group lexical variants of the same verb into semantic classes. Additionally, we analyze differences in verb usage between biomedical and standard English, and between general biomedical texts and a specific sub domain. This verb frequency data can serve as a basis for named entity recognition in biomedical texts.