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Active learning for dependency parsing using partially annotated sentences

Authors:

Seyed Abolghasem Mirroshandel,

Alexis NasrAuthors Info & Claims

IWPT '11: Proceedings of the 12th International Conference on Parsing Technologies

Pages 140 - 149

Published: 05 October 2011 Publication History

Abstract

Current successful probabilistic parsers require large treebanks which are difficult, time consuming, and expensive to produce. Some parts of these data do not contain any useful information for training a parser. Active learning strategies allow to select the most informative samples for annotation. Most existing active learning strategies for parsing rely on selecting uncertain sentences for annotation. We show in this paper that selecting full sentences is not an optimal solution and propose a way to select only subparts of sentences.

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Cited By

Ahangi ALangroudi AYazdanpanah FMirroshandel S(2019)A novel fusion mixture of active experts algorithm for traffic signs recognitionMultimedia Tools and Applications10.1007/s11042-019-7391-078:14(20217-20237)Online publication date: 2-Aug-2019
https://dl.acm.org/doi/10.1007/s11042-019-7391-0
Mirroshandel SNasr ALe Roux JLi HLin COsborne M(2012)Semi-supervised dependency parsing using lexical affinitiesProceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 110.5555/2390524.2390634(777-785)Online publication date: 8-Jul-2012
https://dl.acm.org/doi/10.5555/2390524.2390634

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Information & Contributors

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Published In

cover image DL Hosted proceedings

IWPT '11: Proceedings of the 12th International Conference on Parsing Technologies

October 2011

264 pages

ISBN:9781932432046

General Chair:
Harry Bunt,
Program Chair:
Joakim Nivre

Publisher

Association for Computational Linguistics

United States

Publication History

Published: 05 October 2011

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Cited By

Ahangi ALangroudi AYazdanpanah FMirroshandel S(2019)A novel fusion mixture of active experts algorithm for traffic signs recognitionMultimedia Tools and Applications10.1007/s11042-019-7391-078:14(20217-20237)Online publication date: 2-Aug-2019
https://dl.acm.org/doi/10.1007/s11042-019-7391-0
Mirroshandel SNasr ALe Roux JLi HLin COsborne M(2012)Semi-supervised dependency parsing using lexical affinitiesProceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 110.5555/2390524.2390634(777-785)Online publication date: 8-Jul-2012
https://dl.acm.org/doi/10.5555/2390524.2390634

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