Semi-Markovbased algorithms, such as semi-Markov perceptron and semi-Markov CRFs, enumerate NE candidates represented by word chunks in advance for capturing features such as the first word of a chunk and the last word of a chunk.
the computational cost of a semi-Markov perceptron is O(KLN ), where L is the upper bound length of the entities.