Although "PropBank" refers to a specific corpus produced by Martha Palmer et al.,[1] the term propbank is also coming to be used as a common noun referring to any corpus that has been annotated with propositions and their arguments.
PropBank is a verb-oriented resource, while FrameNet is centered on the more abstract notion of frames, which generalizes descriptions across similar verbs (e.g. "describe" and "characterize") as well as nouns and other words (e.g.
PropBank commits to annotating all verbs in a corpus, whereas the FrameNet project chooses sets of example sentences from a large corpus and only in a few cases has annotated longer continuous stretches of text.
From the start, PropBank was developed with the idea of serving as training data for machine learning-based semantic role labeling systems in mind.
[3] Due to such differences, semantic role labeling with respect to PropBank is often a somewhat easier task than producing FrameNet-style annotations.