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Learning Script Participants from Unlabeled Data

  • We introduce a system that learns the participants of arbitrary given scripts. This system processes data from web experiments, in which each participant can be realized with different expressions. It computes participants by encoding semantic similarity and global structural information into an Integer Linear Program. An evaluation against a gold standard shows that we significantly outperform two informed baselines.

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Metadaten
Author:Michaela Regneri, Alexander Koller, Josef RuppenhoferGND, Manfred Pinkal
URN:urn:nbn:de:bsz:mh39-52718
URL:http://www.aclweb.org/anthology/R/R11/
ISSN:1313-8502
Parent Title (English):Proceedings of Recent Advances in Natural Language Processing
Publisher:ICOMANIA Ltd.
Place of publication:Shoumen
Document Type:Conference Proceeding
Language:English
Year of first Publication:2011
Date of Publication (online):2016/09/16
Publicationstate:Veröffentlichungsversion
Reviewstate:Peer-Review
Tag:Integer Linear Program; arbitrary scripts; global structural information; semantic similarity
GND Keyword:Automatische Sprachanalyse; Nominalphrase; Semantische Analyse
First Page:463
Last Page:470
Dewey Decimal Classification:400 Sprache / 410 Linguistik
Linguistics-Classification:Computerlinguistik
Open Access?:Ja
Licence (German):Es gilt das UrhG