Formally, the baseline NB classifier uses the formula: where F is the set of local features, P (PlausFillr (NP i )) is the prior probability, and Z is the normalizing constant.
to the MUC-4 data, this improvement was mostly due to an increase in precision (up to 0.41), indicating that our unified IE model was effective at eliminating many false hits.