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This is a review of [[reviewed paper::Krishnan_2006_an_effective_two_stage_model_for_exploiting_non_local_dependencies_in_named_entity_recognition]] by [[reviewer::user:Ironfoot]]. * Upgrade of non-local feature CRF ** Soft contraint of consistency among long distance similar tokens ** No need of approximate inference * Statistics of label consistency in document level and corpus level ** Good and detail starting point for raising the issue * Two step CRF ** First step: normal CRF ** Second step: CRF with non-local features derived from first step *** In general dividing the problem into sequential steps may lead error propogation. But in this case it is error correction. Interesting

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