The WEB1T-n-GRAM-R uses none of the local context to decide which features to provide, and the NB-R uses only the immediate left and right context, so both models ignore most of the context.
the remaining graphical models use Viterbi decoding to take into account all tokens in the surrounding sentence, which helps to explain their relative improvement over WEB1T-n-GRAM-R on polysemous words.