Representing the probability of DOD as θ, after n occurrences of the verb the probability that y of them are DOD is: Considering that p(y| θ, n) is the likelihood in a Bayesian framework, the simplest and the most intuitive estimator of θ, given y in n verb occurrences, is the Maximum Likelihood Estimator (MLE): θ MLE is viable as a learning model in the sense that its accuracy increases as the amount of evidence for a verb grows (n → ∞), reflecting the incremental, on-line character of language learning.
one well known limitation of MLE is that it assigns zero probability mass to unseen events.