Inferring textual entailment with a probabilistically sound calculus

Harmeling, S

doi:10.1017/S1351324909990118

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Inferring textual entailment with a probabilistically sound calculus

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Harmeling, S
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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https://www.cambridge.org/core/journals/natural-language-engineering/article/inferring-textual-entailment-with-a-probabilistically-sound-calculus/8862467AF869629E6A572D5CC03DAC34
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Citation

Harmeling, S. (2009). Inferring textual entailment with a probabilistically sound calculus. Natural Language Engineering, 15(4), 459-477. doi:10.1017/S1351324909990118.

Cite as: https://hdl.handle.net/11858/00-001M-0000-0013-C25E-7

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.