Syntactic Parsing for Ranking-Based Coreference Resolution

Altaf Rahman and Vincent Ng.
Proceedings of the 5th International Joint Conference on Natural Language Processing, pp. 465-473, 2011.

Click here for the PostScript or PDF version. The talk slides are available here.

Abstract

Recent research efforts have led to the development of a state-of-the-art supervised coreference model, the cluster-ranking model. However, it is not clear whether the features that have been shown to be useful when employed in traditional coreference models will fare equally well in this new model. Rather than merely re-evaluate them using the cluster-ranking model, we examine two interesting types of features derived from syntactic parses, tree-based features and path-based features, and discuss the challenges involved in employing them in the cluster-ranking model. Experimental results on a set of Switchboard dialogues show their effectiveness when used in combination with the cluster-ranking model: using them to augment a baseline coreference feature set results in a 8.6-11.7% reduction in relative error.

BibTeX entry

@InProceedings{Rahman+Ng:11d,
  author = {Altaf Rahman and Vincent Ng},
  title = {Syntactic Parsing for Ranking-Based Coreference Resolution},
  booktitle = {Proceedings of the 5th International Joint Conference on Natural Language Processing},
  pages = {465--473},
  year = 2011
}