A pattern learning approach to question answering within the ephyra framework

Authors:
Nico Schlaefer;Petra Gieselmann;Thomas Schaaf;Alex Waibel
Affiliations:
Interactive Systems Labs, ITI, Universität Karlsruhe, Karlsruhe, Germany;Interactive Systems Labs, ITI, Universität Karlsruhe, Karlsruhe, Germany;Interactive Systems Labs, Carnegie Mellon University, Pittsburgh, PA;Interactive Systems Labs, ITI, Universität Karlsruhe, Karlsruhe, Germany
Venue:
TSD'06 Proceedings of the 9th international conference on Text, Speech and Dialogue
Year:
2006

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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.