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- W2012180588 abstract "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 paper we investigate two approaches for unsupervised learning of such rules and compare 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." @default.
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- W2012180588 date "2008-01-01" @default.
- W2012180588 modified "2023-10-17" @default.
- W2012180588 title "Learning entailment rules for unary templates" @default.
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- W2012180588 doi "https://doi.org/10.3115/1599081.1599188" @default.
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