AORTE for Recognizing Textual Entailment

Authors:
Reda Siblini;Leila Kosseim
Affiliations:
CLaC laboratory, Department of Computer Science and Software Engineering, Montreal, Canada H3G 1M8;CLaC laboratory, Department of Computer Science and Software Engineering, Montreal, Canada H3G 1M8
Venue:
CICLing '09 Proceedings of the 10th International Conference on Computational Linguistics and Intelligent Text Processing
Year:
2009

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Abstract

In this paper we present the use of the AORTE system in recognizing textual entailment. AORTE allows the automatic acquisition and alignment of ontologies from text. The information resulted from aligning ontologies created from text fragments is used in classifying textual entailment. We further introduce the set of features used in classifying textual entailment. At the TAC RTE4 challenge the system evaluation yielded an accuracy of 68% on the two-way task, and 61% on the three way task using a simple decision tree classifier.