  Most, if not all forms of ellipsis (e.g., so does Mary) are similar to
reading comprehension questions (what does Mary do), in that in order to
resolve them, we need to identify an appropriate text span in the preceding
discourse. Following this observation, we present an alternative approach for
English ellipsis resolution relying on architectures developed for question
answering (QA). We present both single-task models, and joint models trained on
auxiliary QA and coreference resolution datasets, clearly outperforming the
current state of the art for Sluice Ellipsis (from 70.00 to 86.01 F1) and Verb
Phrase Ellipsis (from 72.89 to 78.66 F1).
