Recognizing textual entailment using a machine learning approach

Authors:
Miguel Angel Ríos Gaonac;Alexander Gelbukh;Sivaji Bandyopadhyay
Affiliations:
Center for Computing Research, National Polytechnic Institute, Mexico;Center for Computing Research, National Polytechnic Institute, Mexico;Computer Science & Engineering Department, Jadavpur University, Kolkata, India
Venue:
MICAI'10 Proceedings of the 9th Mexican international conference on Artificial intelligence conference on Advances in soft computing: Part II
Year:
2010

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Abstract

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.