Unsupervised learning of semantic relation composition

Authors:
Eduardo Blanco;Dan Moldovan
Affiliations:
The University of Texas at Dallas, Richardson, TX;The University of Texas at Dallas, Richardson, TX
Venue:
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Year:
2011

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Abstract

This paper presents an unsupervised method for deriving inference axioms by composing semantic relations. The method is independent of any particular relation inventory. It relies on describing semantic relations using primitives and manipulating these primitives according to an algebra. The method was tested using a set of eight semantic relations yielding 78 inference axioms which were evaluated over PropBank.