A Markov chain is an edge-labelled directed graph, where
each node represents a "state", e.g. a lexical category,
and the edge-labels are probabilities of moving the state
at the end of the directed arc.
To convert our example into a Hidden Markov Model (HMM), we would need to add to each node a table of output probabilities, in this case lexical generation probabilities - e.g. if one is in state N, what are the probabilities of producing each possible noun when in this state.