COREFERENCE RESOLUTION STRATEGIES FROM AN APPLICATION PERSPECTIVE

As part of our TIPSTER III research program, we have continued our research into strategies to resolve coreferences within a free text document; this research was begun during our TIPSTER II research program. In the TIPSTER II Proceedings paper, "An Evaluation of Coreference Resolution Strategies for Acquiring Associated Information," the goal was to evaluate the contributions of various techniques for associating an entity with three types of information: 1) name variations, 2) descriptive phrases, and 3) location information. This paper discusses the evolution of the coreference resolution techniques of the NLToolset, as they have been applied to an information extraction application, similar to the MUC Scenario Template task. Development of this application motivated new coreference resolution algorithms which were specific to the type of entity being handled. It also has raised the importance of understanding the structure of a document in order to guide the coreference resolution process.