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Multilingual Supervision of Semantic Annotation

Exner, Peter LU ; Klang, Marcus LU orcid and Nugues, Pierre LU orcid (2016) 26th International Conference on Computational Linguistics (COLING), 2016 p.1007-1017
Abstract
In this paper, we investigate the annotation projection of semantic units in a practical setting. Previous approaches have focused on using parallel corpora for semantic transfer. We evaluate an alternative approach using loosely parallel corpora that does not require the corpora to be exact translations of each other. We developed a method that transfers semantic annotations from one language to another using sentences aligned by entities, and we extended it to include alignments by entity-like linguistic units. We conducted our experiments on a large scale using the English, Swedish, and French language editions of Wikipedia. Our results show that the annotationprojectionusingentitiesincombinationwithlooselyparallelcorporaprovidesaviable... (More)
In this paper, we investigate the annotation projection of semantic units in a practical setting. Previous approaches have focused on using parallel corpora for semantic transfer. We evaluate an alternative approach using loosely parallel corpora that does not require the corpora to be exact translations of each other. We developed a method that transfers semantic annotations from one language to another using sentences aligned by entities, and we extended it to include alignments by entity-like linguistic units. We conducted our experiments on a large scale using the English, Swedish, and French language editions of Wikipedia. Our results show that the annotationprojectionusingentitiesincombinationwithlooselyparallelcorporaprovidesaviable approach to extending previous attempts. In addition, it allows the generation of proposition banks upon which semantic parsers can be trained. (Less)
Please use this url to cite or link to this publication:
author
; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
pages
1007 - 1017
conference name
26th International Conference on Computational Linguistics (COLING), 2016
conference location
Osaka, Japan
conference dates
2016-12-11 - 2016-12-16
external identifiers
  • scopus:85054960232
ISBN
978-4-87974-702-0
language
English
LU publication?
yes
id
cea64b56-c8d1-4cee-936b-4c740b39c123
alternative location
http://semantica.cs.lth.se/coling2016-exner-cr.pdf
date added to LUP
2016-12-07 17:00:18
date last changed
2025-04-04 14:19:36
@inproceedings{cea64b56-c8d1-4cee-936b-4c740b39c123,
  abstract     = {{In this paper, we investigate the annotation projection of semantic units in a practical setting. Previous approaches have focused on using parallel corpora for semantic transfer. We evaluate an alternative approach using loosely parallel corpora that does not require the corpora to be exact translations of each other. We developed a method that transfers semantic annotations from one language to another using sentences aligned by entities, and we extended it to include alignments by entity-like linguistic units. We conducted our experiments on a large scale using the English, Swedish, and French language editions of Wikipedia. Our results show that the annotationprojectionusingentitiesincombinationwithlooselyparallelcorporaprovidesaviable approach to extending previous attempts. In addition, it allows the generation of proposition banks upon which semantic parsers can be trained.}},
  author       = {{Exner, Peter and Klang, Marcus and Nugues, Pierre}},
  booktitle    = {{Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers}},
  isbn         = {{978-4-87974-702-0}},
  language     = {{eng}},
  pages        = {{1007--1017}},
  title        = {{Multilingual Supervision of Semantic Annotation}},
  url          = {{http://semantica.cs.lth.se/coling2016-exner-cr.pdf}},
  year         = {{2016}},
}