A Machine Learning Approach to Identification and Resolution of One-Anaphora
Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence. Pages 1105-1109.
Abstract
We present a machine learning approach to identifying and resolving one-anaphora. In this approach, the system first learns to distinguish different uses of instances of the word one; in the second stage, the antecedents of those instances of one that are classified as anaphoric are then determined. We evaluated our approach on written texts drawn from the informative domains of the British National Corpus (BNC), and achieved encouraging results. To our knowledge, this is the first learningbased system for the identification and resolution of one-anaphora.
@inproceedings{ijcai2005p215,
title = {A Machine Learning Approach to Identification and Resolution of One-Anaphora},
author = {Ng, Hwee Tou and Zhou, Yu and Dale, Robert and Gardiner, Mary},
booktitle = {Proceedings of the Nineteenth International Joint Conference on
Artificial Intelligence, {IJCAI-05}},
publisher = {International Joint Conferences on Artificial Intelligence},
pages = {1105--1109},
year = {2005},
url = {https://ijcai.org/proceedings/2005/215},
}
TY - CPAPER TI - A Machine Learning Approach to Identification and Resolution of One-Anaphora AU - Ng, Hwee Tou AU - Zhou, Yu AU - Dale, Robert AU - Gardiner, Mary T2 - Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, IJCAI-05 PB - International Joint Conferences on Artificial Intelligence PY - 2005 SP - 1105 EP - 1109 UR - https://ijcai.org/proceedings/2005/215 ER -Copied
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