This paper contributes a formalization of frame-semantic parsing as a structure prediction problem and describes an implemented
parser that transforms an English sentence into a frame-semantic representation. It ﬁnds words that evoke FrameNet frames, selects
frames for them, and locates the arguments for each frame. The system uses two featurebased, discriminative probabilistic (log-linear)
models, one with latent variables to permit disambiguation of new predicate words. The parser is demonstrated to signiﬁcantly outperform previously published results.