Feature Generation for Robust Semantic Role Labeling
Table 1: Performance of our automatic feature selection vs prior work. In general our local model with automatic feature selection is a few points behind joint inference models but matches or exceeds other local inference models. Results for FrameNet are on top, Propbank below.
['[EMPTY]', 'Global', 'P', 'R', 'F1']
Overall, our method seems to work about as well as experts manually designing features for SRL. Other systems achieve better performance, but these models all use global information, an orthogonal issue to the local feature set.