1. 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. Content Type Book ChapterDOI 10.1007/978-3-642-16773-7_15Authors Miguel Angel Ríos Gaona, Center for Computing Research, National Polytechnic Institute, MexicoAlexander Gelbukh, Center for Computing Research, National Polytechnic Institute, MexicoSivaji Bandyopadhyay, Computer Science & Engineering Department, Jadavpur University, Kolkata, 700 032 ...
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      Discourse, Entailment, Machine Translation, NER, Parsing, Segmentation, Semantic, Sentiment, Summarization, WSD
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