Qualitative dimensions in question answering: extending the definitional QA task

Authors:
Lucian Vlad Lita;Andrew Hazen Schlaikjer;WeiChang Hong;Eric Nyberg
Affiliations:
Computer Science Department, Carnegie Mellon University, Pittsburgh, PA;Computer Science Department, Carnegie Mellon University, Pittsburgh, PA;Computer Science Department, Carnegie Mellon University, Pittsburgh, PA;Computer Science Department, Carnegie Mellon University, Pittsburgh, PA
Venue:
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 4
Year:
2005

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Abstract

Current question answering tasks handle definitional questions by seeking answers which are factual in nature. While factual answers are a very important component in defining entities, a wealth of qualitative data is often ignored. In this incipient work, we define qualitative dimensions (credibility, sentiment, contradictions etc.) for evaluating answers to definitional questions and we explore potential benefits to users. These qualitative dimensions are leveraged to uncover indirect and implicit answers and can help satisfy the user's information need.