  The common practice in coreference resolution is to identify and evaluate the
maximum span of mentions. The use of maximum spans tangles coreference
evaluation with the challenges of mention boundary detection like prepositional
phrase attachment. To address this problem, minimum spans are manually
annotated in smaller corpora. However, this additional annotation is costly and
therefore, this solution does not scale to large corpora. In this paper, we
propose the MINA algorithm for automatically extracting minimum spans to
benefit from minimum span evaluation in all corpora. We show that the extracted
minimum spans by MINA are consistent with those that are manually annotated by
experts. Our experiments show that using minimum spans is in particular
important in cross-dataset coreference evaluation, in which detected mention
boundaries are noisier due to domain shift. We will integrate MINA into
https://github.com/ns-moosavi/coval for reporting standard coreference scores
based on both maximum and automatically detected minimum spans.
