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We propose a novel factor graph model for argument mining, designed for settings in which the argumentative relations in a document do not necessarily form a tree structure. (This is the case in over 20% of the web comments dataset we release.) Our model jointly learns elementary unit type classification and argumentative relation prediction. Moreover, our model supports SVM and RNN parametrizations, can enforce structure constraints (e.g., transitivity), and can express dependencies betweendoi:10.18653/v1/p17-1091 dblp:conf/acl/NiculaePC17 fatcat:byjozupc6bed7pukyovgkbxoaa