Combining Classification-centered and Relation-based Argument Mining Methods.

. Two key tasks in argument mining (AM) are classification of argument components and identification of relations between argument components. Approaches to solving the argument component classification problem typically take a supervised learning approach, however a lack of suitable datasets makes this a challenge for identification of ar-gument component relations. We propose a pipeline with a recurrent, branched structure that combines supervised learning of argument component classifications with NLP approaches to identification of argument component relations, with the aim of improving both classification of argument components (i