  The lack of annotated data on professional argumentation and complete
argumentative debates has led to the oversimplification and the inability of
approaching more complex natural language processing tasks. Such is the case of
the automatic debate evaluation. In this paper, we propose an original hybrid
method to automatically evaluate argumentative debates. For that purpose, we
combine concepts from argumentation theory such as argumentation frameworks and
semantics, with Transformer-based architectures and neural graph networks.
Furthermore, we obtain promising results that lay the basis on an unexplored
new instance of the automatic analysis of natural language arguments.
