This initialization procedure takes the output of the analyzer and assigns a conditional probability distribution P(tag|word) for each word.
it assigns an a priori, context-free likelihood for each analysis of a word (although the word broke can be either a verb in the past tense or an adjective, it is more likely to be the former; such preferences can be modeled as probability distributions, and the initialization procedure attempts to learn the values of these distributions automatically from raw data).