Textual entailment recognition using a linguistically–motivated decision tree classifier

Authors:
Eamonn Newman;Nicola Stokes;John Dunnion;Joe Carthy
Affiliations:
School of Computer Science and Informatics, University College Dublin, Ireland;NICTA Victoria Laboratory, Department of Computer Science and Software Engineering, University of Melbourne, Australia;School of Computer Science and Informatics, University College Dublin, Ireland;School of Computer Science and Informatics, University College Dublin, Ireland
Venue:
MLCW'05 Proceedings of the First international conference on Machine Learning Challenges: evaluating Predictive Uncertainty Visual Object Classification, and Recognizing Textual Entailment
Year:
2005

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Abstract

In this paper we present a classifier for Recognising Textual Entailment (RTE) and Semantic Equivalence. We evaluate the performance of this classifier using an evaluation framework provided by the PASCAL RTE Challenge Workshop. Sentence–pairs are represented as a set of features, which are used by our decision tree classifier to determine if an entailment relationship exisits between each sentence–pair in the RTE test corpus.