Inferring textual entailment with a probabilistically sound calculus*

Authors:
Stefan Harmeling
Affiliations:
Max planck institute for biological cybernetics, spemannstraße 38, 72076 tuebingen, germany e-mail: stefan.harmeling@tuebingen.mpg.de
Venue:
Natural Language Engineering
Year:
2009

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Abstract

We introduce a system for textual entailment that is based on a probabilistic model of entailment. The model is defined using a calculus of transformations on dependency trees, which is characterized by the fact that derivations in that calculus preserve the truth only with a certain probability. The calculus is successfully evaluated on the datasets of the PASCAL Challenge on Recognizing Textual Entailment.