Recognizing Textual Entailment Using a Machine Learning Approach

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. Keywords. Recognizing Textual Entailment, text similarity measures, nonsymmetric measures.

• Type: Journal
• Year: 2010
• Where: MICAI
• Authors: Miguel Angel Ríos Gaona, Alexander F. Gelbukh, Sivaji Bandyopadhyay
• Keywords: Artificial Intelligence, Entailment, MICAI 2010, Similarity Measure, Textual Entailment