Abstract
This paper is about our approach to answer validation, which centered by a Recognizing Textual Entailment (RTE) core engine. We first combined the question and the answer into Hypothesis (H) and view the document as Text (T); then, we used our RTE system to check whether the entailment relation holds between them. Our system was evaluated on the Answer Validation Exercise (AVE) task and achieved f-measures of 0.46 and 0.55 for two submission runs, which both outperformed others' results for the English language. © 2008 Springer-Verlag Berlin Heidelberg.
Cite
CITATION STYLE
Wang, R., & Neumann, G. (2008). Using Recognizing Textual Entailment as a Core Engine for Answer Validation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5152 LNCS, pp. 387–390). Springer Verlag. https://doi.org/10.1007/978-3-540-85760-0_50
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