Joint Parsing and Semantic Role Labeling

Charles Sutton, Andrew McCallum

Research output: Chapter in Book/Report/Conference proceedingConference contribution


A striking feature of human syntactic processing is that it is context-dependent, that is, it seems to take into account semantic information from the discourse context and world knowledge. In this paper, we attempt to use this insight to bridge the gap between SRL results from gold parses and from automatically-generated parses. To do this, we jointly perform parsing and semantic role labeling, using a probabilistic SRL system to rerank the results of a probabilistic parser. Our current results are negative, because a locally-trained SRL model can return inaccurate probability estimates.
Original languageEnglish
Title of host publicationProceedings of the Ninth Conference on Computational Natural Language Learning (CoNLL-2005)
Place of PublicationAnn Arbor, Michigan
PublisherAssociation for Computational Linguistics
Number of pages4
Publication statusPublished - 1 Jun 2005


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