We present our experiments on Recognizing Textual Entailment based on modeling the entailment relation as a classification problem. As features used to classify the entailment pairs we use a symmetric similarity measure and a non-symmetric similarity measure. Our system achieved an accuracy of 66% on the RTE-3 development dataset (with 10-fold cross validation) and accuracy of 63% on the RTE-3 test dataset. © 2010 Springer-Verlag.
CITATION STYLE
Ríos Gaona, M. A., Gelbukh, A., & Bandyopadhyay, S. (2010). Recognizing textual entailment using a machine learning approach. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6438 LNAI, pp. 177–185). https://doi.org/10.1007/978-3-642-16773-7_15
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