Decompositional Argument Mining: A General Purpose Approach for
Argument Graph Construction
Abstract
This work presents an approach decomposing
propositions into four functional components
and identify the patterns linking those components to determine argument structure. The
entities addressed by a proposition are target
concepts and the features selected to make a
point about the target concepts are aspects.
A line of reasoning is followed by providing
evidence for the points made about the target concepts via aspects. Opinions on target
concepts and opinions on aspects are used to
support or attack the ideas expressed by target
concepts and aspects. The relations between
aspects, target concepts, opinions on target
concepts and aspects are used to infer the argument relations. Propositions are connected
iteratively to form a graph structure. The approach is generic in that it is not tuned for a
specific corpus and evaluated on three different corpora from the literature: AAEC, AMT,
US2016G1tv and achieved an F score of 0.79,
0.77 and 0.64, respectively.