Probabilistic coreference in information extraction

Certain applications require that the out-put of an information extraction system be probabilistic, so that a downstream sys-tem can reliably fuse the output with pos-sibly contradictory information from other sources. In this paper we consider the problem of assigning a probability distri-bution to alternative sets of coreference re-lationships among entity descriptions. We present the results of initial experiments with several approaches to estimating such distributions in an application using SRI’s FASTUS information extraction system.