These graphs suggest that the contribution of the individual feature types (semantic class information, partial patterns or infix words) to the classification performance is relatively minor, but in combination they do give a marked improvement over the base features, at least for some relations like causation and material.
the main contribution of semantic word classes and partial patterns to our method's performance lies not in the final classification step but seems to occur at earlier stages of the process, in the candidate and training data generation steps.