Abstract
This paper describes the Ephyra question answering engine, a modular and extensible framework that allows to integrate multiple approaches to question answering in one system. Our framework can be adapted to languages other than English by replacing language-specific components. It supports the two major approaches to question answering, knowledge annotation and knowledge mining. Ephyra uses the web as a data resource, but could also work with smaller corpora. In addition, we propose a novel approach to question interpretation which abstracts from the original formulation of the question. Text patterns are used to interpret a question and to extract answers from text snippets. Our system automatically learns the patterns for answer extraction, using question-answer pairs as training data. Experimental results revealed the potential of this approach.
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© 2006 Springer-Verlag Berlin Heidelberg
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Schlaefer, N., Gieselmann, P., Schaaf, T., Waibel, A. (2006). A Pattern Learning Approach to Question Answering Within the Ephyra Framework. In: Sojka, P., Kopeček, I., Pala, K. (eds) Text, Speech and Dialogue. TSD 2006. Lecture Notes in Computer Science(), vol 4188. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11846406_86
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DOI: https://doi.org/10.1007/11846406_86
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-39090-9
Online ISBN: 978-3-540-39091-6
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