You can use the HMMDecoder function to decode the parts of speech (adjective, noun, verb, and so on.) for a word set, if the set of phrases or words have been trained using a HMMSupervised or HMMUnsupervisedLearner. Assume that you have a set of phrases (shown in the following table) whose parts of speech are unknown and you have the three trained state tables (initial, state_transition and emission) readily available.
In this example, the parts of speech correspond to the hidden states of the HMM function. There are two hidden states in this example: A(Adjective) and N(noun). HMMDecoder can be used to find these parts of speech.
The following is a table of initial states:
The following is a table of state transitions:
The following is a table of emissions: