  Most of the existing work that focus on the identification of implicit
knowledge in arguments generally represent implicit knowledge in the form of
commonsense or factual knowledge. However, such knowledge is not sufficient to
understand the implicit reasoning link between individual argumentative
components (i.e., claim and premise). In this work, we focus on identifying the
implicit knowledge in the form of argumentation knowledge which can help in
understanding the reasoning link in arguments. Being inspired by the Argument
from Consequences scheme, we propose a semi-structured template to represent
such argumentation knowledge that explicates the implicit reasoning in
arguments via causality. We create a novel two-phase annotation process with
simplified guidelines and show how to collect and filter high-quality implicit
reasonings via crowdsourcing. We find substantial inter-annotator agreement for
quality evaluation between experts, but find evidence that casts a few
questions on the feasibility of collecting high-quality semi-structured
implicit reasoning through our crowdsourcing process. We release our
materials(i.e., crowdsourcing guidelines and collected implicit reasonings) to
facilitate further research towards the structured representation of
argumentation knowledge.
