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I wonder whether there is any advantage of using maximum-entropy Markov model (MEMM), a.k.a. conditional Markov model (CMM) instead of using conditional random fields (CRF) for named-entity recognition, aside from the training cost.

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I don't think MEMM has advantage over CRF. MEMM still have label bias issue while CRF not.

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