  Citing legal opinions is a key part of legal argumentation, an expert task
that requires retrieval, extraction and summarization of information from court
decisions. The identification of legally salient parts in an opinion for the
purpose of citation may be seen as a domain-specific formulation of a highlight
extraction or passage retrieval task. As similar tasks in other domains such as
web search show significant attention and improvement, progress in the legal
domain is hindered by the lack of resources for training and evaluation.
  This paper presents a new dataset that consists of the citation graph of
court opinions, which cite previously published court opinions in support of
their arguments. In particular, we focus on the verbatim quotes, i.e., where
the text of the original opinion is directly reused.
  With this approach, we explain the relative importance of different text
spans of a court opinion by showcasing their usage in citations, and measuring
their contribution to the relations between opinions in the citation graph.
  We release VerbCL, a large-scale dataset derived from CourtListener and
introduce the task of highlight extraction as a single-document summarization
task based on the citation graph establishing the first baseline results for
this task on the VerbCL dataset.
