2020
AAAI
AAAI 2020
What Do You Mean ‘Why?’: Resolving Sluices in Conversations
Abstract
Abstract 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.
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The Questioner
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Keyword Pioneer
— sluice resolution
🐣
Hot Topic Early Bird
— conversational ai
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio
Authors
Keywords
natural language inference
conversational ai
question answering
natural language understanding
dialogue system
conversational question answering
dialogue understanding
ellipsis resolution
semantic frame
pragmatic inference
sluice resolution
conversational ellipsis
baseline architecture
conversational qa
semantic frame retrieval