Each classifier outputs p(z|x i , w z ) for tuples in a given fold during the E-step (equation 2) and is trained (equation 3 i , w z ) in equation 5as the average of the probabilities of the above set of mention classifiers: z are the weights of the mention classifier responsible for fold j.
we can still use EM, but the optimization focuses on maximizing the lower bound of the loglikelihood, i.e., we maximize the above joint probability for each entity pair in the database.