Semantic Role Labeling improves incremental parsing

Ioannis Konstas, Frank Keller

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

2 Citations (Scopus)

Abstract

Incremental parsing is the task of assigning a syntactic structure to an input sentence as it unfolds word by word. Incremental parsing is more difficult than full sentence parsing, as incomplete input increases ambiguity. Intuitively, an incremental parser that has access to semantic information should be able to reduce ambiguity by ruling out semantically implausible analyses, even for incomplete input. In this paper, we test this hypothesis by combining an incremental TAG parser with an incremental semantic role labeler in a discriminative framework. We show a substantial improvement in parsing performance compared to the baseline parser, both in full-sentence F-score and in incremental F-score.
Original languageEnglish
Title of host publicationProceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing
PublisherAssociation for Computational Linguistics
Pages1191-1201
Number of pages11
Volume1
ISBN (Print)9781941643723
Publication statusPublished - 2015
Event53rd Annual Meeting of the Association for Computational Linguistics 2015 - Beijing, China
Duration: 26 Jul 201531 Jul 2015

Conference

Conference53rd Annual Meeting of the Association for Computational Linguistics 2015
Abbreviated titleACL 2015
CountryChina
CityBeijing
Period26/07/1531/07/15

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