Syntactic Parsing for Ranking-Based Coreference Resolution
Altaf Rahman, Vincent Ng · 2011
Recent research efforts have led to the de-velopment 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 similarly when used in combination with this new model. Rather than merely re-evaluate them using the cluster-ranking model, we examine two in-teresting types of features derived from syntactic parses, tree-based features and path-based features, and discuss the chal-lenges involved in employing them in the cluster-ranking model. Results on a set of Switchboard dialogues show their effec-tiveness in improving the cluster-ranking model: using them to augment a baseline coreference feature set yields a 8.6–11.7% reduction in relative error. 1