Carnegie Mellon University
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Probabilistic Frame-Semantic Parsing

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journal contribution
posted on 2010-06-01, 00:00 authored by Dipanjan Das, Nathan Schneider, Desai Chen, Noah A. Smith

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.


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Copyright 2010 ACL



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