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Although information extraction and coreference resolution appear together inmany applications, most current systems perform them as ndependent steps. Thispaper describes an approach to integrated inference for extraction andcoreference based on conditionally-trained undirected graphical models. Wediscuss the advantages of conditional probability training, and of acoreference model structure based on graph partitioning. On a data set ofresearch paper citations, we show significant reduction in error by usingextraction uncertainty to improve coreference citation matching accuracy, andusing coreference to improve the accuracy of the extracted fields.

An Integrated, Conditional Model of Information Extraction and Coreference with Applications to Citation Matching