A machine learning approach to identification and resolution of one-anaphora

Authors:
Hwee Tou Ng;Yu Zhou;Robert Dale;Mary Gardiner
Affiliations:
Department of Computer Science, National University of Singapore, Singapore;Department of Computer Science, National University of Singapore, Singapore;Centre for Language Technology, Macquarie University, Sydney, Australia;Centre for Language Technology, Macquarie University, Sydney, Australia
Venue:
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Year:
2005

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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 learning-based system for the identification and resolution of one-anaphora.