# What Do You Mean `Why?': Resolving Sluices in Conversations

arXiv: https://arxiv.org/abs/1911.09478 · HTML: https://mlsanity.com/paper/1911.09478/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Nov 2019.

## Built on by (most cited first, 2 of 2)

- [Can Question Rewriting Help Conversational Question Answering?](https://mlsanity.com/paper/2204.06239/) (2022)
- [S2M: Converting Single-Turn to Multi-Turn Datasets for Conversational Question Answering](https://mlsanity.com/paper/2312.16511/) (2023)

## Abstract (arXiv)

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.