In testing, unknown words are generated after the generation of symbol UNKNOWN, and we define their probability by a first-order Markov model.
given a flat word w = c 1 c 2 • • • c n not seen in training, we define its probability conditioned with the part-of-speech p as where c 0 is taken to be a START symbol indicating the left boundary of a word and c n+1 is the STOP symbol to indicate the right boundary.