Unfortunately EM is not guaranteed to find a globally optimal model.  Thus good results can be achieved only by starting with a “reasonable” initial HMM, for example assigning very low probabilities to certain transitions (such as determiner → determiner, determiner → verb, adjective → verb). Semi-supervised learning might start with a relatively small labeled training corpus, and use the corresponding HMM parameter estimates as a starting point for unsupervised learning from further, unlabeled texts.  