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Title:Natural Language Inference via Dependency Tree Mapping: An Application to Question Answering
Author(s):Punyakanok, Vasin; Roth, Dan; Yih, Wen-tau
Subject(s):Natural Language Processing
Abstract:We describe an approach for answer selection in a free form question answering task. In order to go beyond a key-word based matching in selecting answers to questions, one would like to develop a principled way for the answer selection process that incorporates both syntactic and semantic information. We achieve this goal by (1) representing both questions and candidate passages using dependency trees, augmented with semantic information such as named entities, and (2) computing a generalized edit distance between a candidate passage representation and the question representation, a distance which aims to capture some level of meaning similarity. The sentence that best answers a question is determined to be the one that minimizes the generalized edit distance we define, computed via a dynamic programming based approximate tree matching algorithm. We evaluate the approach on question-answer pairs taken from previous TREC Q/A competitions. Preliminary experiments show its potential by significantly outperforming common bag-of-word scoring methods.
Issue Date:2004-01
Genre:Technical Report
Other Identifier(s):UIUCDCS-R-2004-2640
Rights Information:You are granted permission for the non-commercial reproduction, distribution, display, and performance of this technical report in any format, BUT this permission is only for a period of 45 (forty-five) days from the most recent time that you verified that this technical report is still available from the University of Illinois at Urbana-Champaign Computer Science Department under terms that include this permission. All other rights are reserved by the author(s).
Date Available in IDEALS:2009-04-20

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