Incremental Semantic Role Labeling with Tree Adjoining Grammar

Ioannis Konstas, Frank Keller, Vera Demberg, Mirella Lapata

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

Abstract / Description of output

We introduce the task of incremental semantic role labeling (iSRL), in which semantic roles are assigned to incomplete input (sentence prefixes). iSRL is the semantic equivalent of incremental parsing, and is useful for language modeling, sentence completion, machine translation, and psycholinguistic modeling. We propose an iSRL system that combines an incremental TAG parser with a semantically enriched lexicon, a role propagation algorithm, and a cascade of classifiers. Our approach achieves an SRL Fscore of 78.38% on the standard CoNLL 2009 dataset. It substantially outperforms a strong baseline that combines gold-standard syntactic dependencies with heuristic role assignment, as well as a baseline based on Nivre’s incremental dependency parser.
Original languageEnglish
Title of host publicationProceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, EMNLP 2014, October 25-29, 2014, Doha, Qatar, A meeting of SIGDAT, a Special Interest Group of the ACL
Number of pages12
Publication statusPublished - Oct 2014


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