In this paper we investigate a novel method to detect asymmetric entailment relations between verbs. Our starting point is the idea that some point-wise verb selectional preferences carry relevant semantic information. Experiments using Word- Net as a gold standard show promising results. Where applicable, our method, used in combination with other approaches, significantly increases the performance of entailment detection. A combined approach including our model improves the AROC of 5% absolute points with respect to standard models.
Zanzotto, F.m., Pennacchiotti, M., Pazienza, M.t. (2006). Discovering asymmetric entailment relations between verbs using selectional preferences. In Proceedings of 44th Annual meeting of the Association for computational linguistics (ACL) - (GGS Conference Rating 1 A++) (pp.849-856). Morristown (NJ, USA) : Association for Computational Linguistics [10.3115/1220175.1220282].
Discovering asymmetric entailment relations between verbs using selectional preferences
ZANZOTTO, FABIO MASSIMO;PAZIENZA, MARIA TERESA
2006-01-01
Abstract
In this paper we investigate a novel method to detect asymmetric entailment relations between verbs. Our starting point is the idea that some point-wise verb selectional preferences carry relevant semantic information. Experiments using Word- Net as a gold standard show promising results. Where applicable, our method, used in combination with other approaches, significantly increases the performance of entailment detection. A combined approach including our model improves the AROC of 5% absolute points with respect to standard models.File | Dimensione | Formato | |
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