Paper: Learning Entailment Rules for Unary Templates

ACL ID C08-1107
Title Learning Entailment Rules for Unary Templates
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2008

Most work on unsupervised entailment rule acquisition focused on rules between templates with two variables, ignoring unary rules - entailment rules between templates with a single variable. In this pa- per we investigate two approaches for un- supervised learning of such rules and com- pare the proposed methods with a binary rule learning method. The results show that the learned unary rule-sets outperform the binary rule-set. In addition, a novel directional similarity measure for learning entailment, termed Balanced-Inclusion, is the best performing measure.