Design Tree based Coreference Resolution

This was the first paper about Design Tree based Coreference Resolution.

Title: Using Decision Tree for Coreference Resolution
Author(s): Joseph F.McCarthy and Wendy G.Lehnert
Author Affiliation: Department of Computer Science, University of Massachusetts
Citation: 26(Citeseer statistical indicates)
ConferenceTitle: the Fourteenth Internation Joint Conference on Artificial Intelligence(IJCAI '95)
Language: English
Type: Conference Paper (PA)
Treatment: Practical (P) Experimental (X)

Abstract: This paper describes RESOLVE, a system that uses decision trees to learn how to classify coreferent phrase in the domain of business joint ventures. An experiment is presented in which the performance of RESOLVE is compared to the performance of a mannually engineered set of rules for the same task. The results show that decision trees achieve higher performance than the rules in two of three evaluation metrics developed for the coreference task. In addition to achieving better performancethan the rules.RESOLVE provides a framework that facilitates the exploration of the type of knowledge that are useful for solving the corederence pronlem.

Descriptors: Information Extraction
Identifiers: coreference resolution, design tree


And the personal view about this paper was that I thought we could have a try in Chinese based on and improving this framework.