Natural Language Engineering



Natural language question answering: the view from here


L. HIRSCHMAN a1 and R. GAIZAUSKAS a2
a1 The MITRE Corporation, Bedford, MA, USA
a2 Department of Computer Science, University of Sheffield, Sheffield, UK e-mail: r.gaizayskas@dcs.shef.ac.uk

Abstract

As users struggle to navigate the wealth of on-line information now available, the need for automated question answering systems becomes more urgent. We need systems that allow a user to ask a question in everyday language and receive an answer quickly and succinctly, with sufficient context to validate the answer. Current search engines can return ranked lists of documents, but they do not deliver answers to the user.

Question answering systems address this problem. Recent successes have been reported in a series of question-answering evaluations that started in 1999 as part of the Text Retrieval Conference (TREC). The best systems are now able to answer more than two thirds of factual questions in this evaluation.