Correcting prepositional phrase attachments using multimodal corpora

Sebastien Delecraz, Alexis Nasr, Frederic Bechet, Benoit Favre


Abstract
PP-attachments are an important source of errors in parsing natural language. We propose in this article to use data coming from a multimodal corpus, combining textual, visual and conceptual information, as well as a correction strategy, to propose alternative attachments in the output of a parser.
Anthology ID:
W17-6311
Volume:
Proceedings of the 15th International Conference on Parsing Technologies
Month:
September
Year:
2017
Address:
Pisa, Italy
Editors:
Yusuke Miyao, Kenji Sagae
Venue:
IWPT
SIG:
SIGPARSE
Publisher:
Association for Computational Linguistics
Note:
Pages:
72–77
Language:
URL:
https://aclanthology.org/W17-6311
DOI:
Bibkey:
Cite (ACL):
Sebastien Delecraz, Alexis Nasr, Frederic Bechet, and Benoit Favre. 2017. Correcting prepositional phrase attachments using multimodal corpora. In Proceedings of the 15th International Conference on Parsing Technologies, pages 72–77, Pisa, Italy. Association for Computational Linguistics.
Cite (Informal):
Correcting prepositional phrase attachments using multimodal corpora (Delecraz et al., IWPT 2017)
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PDF:
https://aclanthology.org/W17-6311.pdf
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