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This is a review of [[reviewed paper::Cohn_2005_semantic_role_labelling_with_tree_conditional_random_fields]] by [[reviewer::user:Ironfoot]]. * CRF on tree structure * Data representation ** Pruned tree: reduce size ** Constituents children labeling (new inside or parent's argument label) *** new inside label is better ** What is 'argument'? I don't understand this part very well * Model ** 1-node, 2-node feature ** Use only 1-node feature to mimic maxent * Result ** There are no comparisons ** Where is the result for the preliminary case?

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