A Machine Learning Approach to Identification and Resolution of One-Anaphora

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. 1

Cite

Text

Ng et al. "A Machine Learning Approach to Identification and Resolution of One-Anaphora." International Joint Conference on Artificial Intelligence, 2005.

Markdown

[Ng et al. "A Machine Learning Approach to Identification and Resolution of One-Anaphora." International Joint Conference on Artificial Intelligence, 2005.](https://mlanthology.org/ijcai/2005/ng2005ijcai-machine/)

BibTeX

@inproceedings{ng2005ijcai-machine,
  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 = {International Joint Conference on Artificial Intelligence},
  year      = {2005},
  pages     = {1105-1110},
  url       = {https://mlanthology.org/ijcai/2005/ng2005ijcai-machine/}
}