Given P (l=1|e, k, c), the goal of the M-step is to (re)estimate two of the four groups of parameters mentioned above, namely P (e t |c t , l=1) and P (f i c |l), using maximum likelihood estimation.
p (e t |c t , l=1) is estimated as follows: where Count(c t , l=1) is the expected number of times c has trigger word c t when it is the antecedent of an event mention; and |t| is the number of possible trigger words in the training data (we treat the "trigger word" of a dummy candidate antecedent as an unseen word).