We conclude that when the model is provided with syntactic information, it learns to pick S-type candidates, but does not continue to learn deeper features to further distinguish them or needs more data to do so.
the model is not able to point to exactly one antecedent, resulting in a lower s@1 score, but does well in picking a few good candidates, which yields good s@2-4 scores.