Question Answering

Sanda Harabagiu and Dan Moldovan

in The Oxford Handbook of Computational Linguistics

Published in print January 2005 | ISBN: 9780199276349
Published online September 2012 | e-ISBN: 9780191743573 | DOI:

Series: Oxford Handbooks in Linguistics

 Question Answering

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  • Computational Linguistics
  • Pragmatics


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Textual Question Answering (QA) identifies the answer to a question in large collections of on-line documents. By providing a small set of exact answers to questions, QA takes a step closer to information retrieval rather than document retrieval. A QA system comprises three modules: a question-processing module, a document-processing module, and an answer extraction and formulation module. Questions may be asked about any topic, in contrast with Information Extraction (IE), which identifies textual information relevant only to a predefined set of events and entities. The natural language processing (NLP) techniques used in open-domain QA systems may range from simple lexical and semantic disambiguation of question stems to complex processing that combines syntactic and semantic features of the questions with pragmatic information derived from the context of candidate answers. This article reviews current research in integrating knowledge-based NLP methods with shallow processing techniques for QA.

Keywords: textual question answering; information retrieval; document retrieval; question-answer system; natural language processing; lexical and semantic disambiguation; syntactic and semantic features

Article.  8018 words. 

Subjects: Computational Linguistics ; Pragmatics

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