  In conversation, we often ask one-word questions such as `Why?' or `Who?'.
Such questions are typically easy for humans to answer, but can be hard for
computers, because their resolution requires retrieving both the right semantic
frames and the right arguments from context. This paper introduces the novel
ellipsis resolution task of resolving such one-word questions, referred to as
sluices in linguistics. We present a crowd-sourced dataset containing
annotations of sluices from over 4,000 dialogues collected from conversational
QA datasets, as well as a series of strong baseline architectures.
