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Using cross-lingual projections to generate semantic role labeled corpus for Urdu: a resource poor language

Authors:

Smruthi Mukund,

Debanjan Ghosh,

Rohini K. SrihariAuthors Info & Claims

COLING '10: Proceedings of the 23rd International Conference on Computational Linguistics

Pages 797 - 805

Published: 23 August 2010 Publication History

Abstract

In this paper we explore the possibility of using cross lingual projections that help to automatically induce role-semantic annotations in the PropBank paradigm for Urdu, a resource poor language. This technique provides annotation projections based on word alignments. It is relatively inexpensive and has the potential to reduce human effort involved in creating semantic role resources. The projection model exploits lexical as well as syntactic information on an English-Urdu parallel corpus. We show that our method generates reasonably good annotations with an accuracy of 92% on short structured sentences. Using the automatically generated annotated corpus, we conduct preliminary experiments to create a semantic role labeler for Urdu. The results of the labeler though modest, are promising and indicate the potential of our technique to generate large scale annotations for Urdu.

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Cited By

(2017)Modeling of learning curves with applications to POS taggingComputer Speech and Language10.1016/j.csl.2016.06.00141:C(1-28)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.1016/j.csl.2016.06.001
Syed AAslam MMartinez-Enriquez A(2011)Sentiment analysis of urdu languageProceedings of the 10th Mexican international conference on Advances in Artificial Intelligence - Volume Part I10.1007/978-3-642-25324-9_33(382-393)Online publication date: 26-Nov-2011
https://dl.acm.org/doi/10.1007/978-3-642-25324-9_33

Using cross-lingual projections to generate semantic role labeled corpus for Urdu: a resource poor language

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Published In

cover image DL Hosted proceedings

COLING '10: Proceedings of the 23rd International Conference on Computational Linguistics

August 2010

1408 pages

General Chair:
Aravind K. Joshi
University of Pennsylvania
,
Program Chairs:
Chu-Ren Huang
The Hong Kong Polytechnic University
,
Dan Jurafsky
Stanford University

Publisher

Association for Computational Linguistics

United States

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Published: 23 August 2010

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Cited By

(2017)Modeling of learning curves with applications to POS taggingComputer Speech and Language10.1016/j.csl.2016.06.00141:C(1-28)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.1016/j.csl.2016.06.001
Syed AAslam MMartinez-Enriquez A(2011)Sentiment analysis of urdu languageProceedings of the 10th Mexican international conference on Advances in Artificial Intelligence - Volume Part I10.1007/978-3-642-25324-9_33(382-393)Online publication date: 26-Nov-2011
https://dl.acm.org/doi/10.1007/978-3-642-25324-9_33

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