Their shallow parse-based system achieved 60.4% precision and 51.4% recall and their full system achieved 80.6% precision and 67.1% recall on the same data set (but 84% precision and 75% recall with the full data set).
due to the use of different architectures and data set sizes, the questions of "how much one can gain from full parsing over shallow parsing when using the full PropBank data set" and "what are the sources of the performance gain" were left open.