In general, the two results reflect the different goals of the two approaches: [1] are interested in investigating and adopting unsupervised techniques with poor semantic and syntactic information to automatically annotate a large scale (but noisy) training set and exploit it for semantic role labelling.
we are interested in developing annotated resources with nearly manual quality, so we consider particularly important FE transfer precision.