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

2 Citations (Scopus)

Abstract

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)
PublisherAssociation for Computational Linguistics
Pages301-312
Number of pages12
ISBN (Electronic)9781937284961
Publication statusPublished - 2014
Event2014 Conference on Empirical Methods in Natural Language Processing - Doha, Qatar
Duration: 25 Oct 201429 Oct 2014

Conference

Conference2014 Conference on Empirical Methods in Natural Language Processing
Abbreviated titleEMNLP 2014
CountryQatar
CityDoha
Period25/10/1429/10/14

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    Konstas, I., Keller, F., Demberg, V., & Lapata, M. (2014). Incremental Semantic Role Labeling with Tree Adjoining Grammar. In Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP) (pp. 301-312). Association for Computational Linguistics. https://www.aclweb.org/anthology/D14-1036