  Explicating implicit reasoning (i.e. warrants) in arguments is a
long-standing challenge for natural language understanding systems. While
recent approaches have focused on explicating warrants via crowdsourcing or
expert annotations, the quality of warrants has been questionable due to the
extreme complexity and subjectivity of the task. In this paper, we tackle the
complex task of warrant explication and devise various methodologies for
collecting warrants. We conduct an extensive study with trained experts to
evaluate the resulting warrants of each methodology and find that our
methodologies allow for high-quality warrants to be collected. We construct a
preliminary dataset of 6,000 warrants annotated over 600 arguments for 3
debatable topics. To facilitate research in related downstream tasks, we
release our guidelines and preliminary dataset.
