An automated method to build a corpus of rhetorically-classified sentences in biomedical texts
Hospice Houngbo, Robert E. Mercer · 2014
The rhetorical classification of sentences in biomedical texts is an important task in the recognition of the components of a scientific argument.Generating supervised machine learned models to do this recognition requires corpora annotated for the rhetorical categories Introduction (or Background), Method, Result, Discussion (or Conclusion).Currently, a few, small annotated corpora exist.We use a straightforward feature of co-referring text using the word "this" to build a selfannotating corpus extracted from a large biomedical research paper dataset.The corpus is annotated for all of the rhetorical categories except Introduction without involving domain experts.In a 10-fold cross-validation, we report an overall Fscore of 97% with Naïve Bayes and 98.7% with SVM, far above those previously reported.