This paper has presented new experimental methodologies and results for cross-document information fusion, focusing on the task of biographic fact extraction and has proposed a new method for crossfield bootstrapping.
we have shown that automatic annotation can be used effectively to train statistical information extractors such Naïve Bayes and CRFs, and that CRF extraction accuracy can be improved by 5% with a negative example model.