Carnegie Mellon University
Browse
file.pdf (358.16 kB)

Probabilistic Frame-Semantic Parsing

Download (358.16 kB)
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.

History

Publisher Statement

Copyright 2010 ACL

Date

2010-06-01

Usage metrics

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC