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. © 2006 Association for Computational Linguistics.
CITATION STYLE
Zanzotto, F. M., Pennacchiotti, M., & Pazienza, M. T. (2006). Discovering asymmetric entailment relations between verbs using selectional preferences. In COLING/ACL 2006 - 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Vol. 1, pp. 849–856). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1220175.1220282
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