 Most sequence labeling algorithms are probabilistic in nature, relying on statistical inference to find the best sequence.The most common statistical models in use for sequence labeling make a Markov assumption, i.e.that the choice of label for a particular word is directly dependent only on the immediately adjacent labels; hence the set of labels forms a Markov chain.