As the small amount of available training data limits the development of robust systems to automatically detect comparisons, this paper investigates how to use semi-supervised strategies to expand a small set of labeled sentences.
we use structural alignment, a method that starts out from a seed set of manually annotated data and finds similar unlabeled sentences to which the labels can be projected.