Abstract
In this paper we define a measure for textual entailment recognition based on structural isomorphism theory applied to lexical dependency information. We describe the experiments carried out to estimate measure’s parameters with logistic regression and SVM. The results obtained show how a model constructed around lexical relationships is a plausible alternative for textual entailment recognition.
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© 2008 Springer-Verlag Berlin Heidelberg
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Uribe, D. (2008). Textual Entailment Recognition Based on Structural Isomorphism. In: Gelbukh, A., Morales, E.F. (eds) MICAI 2008: Advances in Artificial Intelligence. MICAI 2008. Lecture Notes in Computer Science(), vol 5317. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88636-5_20
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DOI: https://doi.org/10.1007/978-3-540-88636-5_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-88635-8
Online ISBN: 978-3-540-88636-5
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