Transferring Semantic Roles Using Translation and Syntactic Information

Maryam Aminian, Mohammad Sadegh Rasooli, Mona Diab


Abstract
Our paper addresses the problem of annotation projection for semantic role labeling for resource-poor languages using supervised annotations from a resource-rich language through parallel data. We propose a transfer method that employs information from source and target syntactic dependencies as well as word alignment density to improve the quality of an iterative bootstrapping method. Our experiments yield a 3.5 absolute labeled F-score improvement over a standard annotation projection method.
Anthology ID:
I17-2003
Volume:
Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers)
Month:
November
Year:
2017
Address:
Taipei, Taiwan
Venue:
IJCNLP
SIG:
Publisher:
Asian Federation of Natural Language Processing
Note:
Pages:
13–19
Language:
URL:
https://aclanthology.org/I17-2003
DOI:
Bibkey:
Cite (ACL):
Maryam Aminian, Mohammad Sadegh Rasooli, and Mona Diab. 2017. Transferring Semantic Roles Using Translation and Syntactic Information. In Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers), pages 13–19, Taipei, Taiwan. Asian Federation of Natural Language Processing.
Cite (Informal):
Transferring Semantic Roles Using Translation and Syntactic Information (Aminian et al., IJCNLP 2017)
Copy Citation:
PDF:
https://aclanthology.org/I17-2003.pdf