Paper: Unsupervised Learning of Semantic Relation Composition

ACL ID P11-1146
Title Unsupervised Learning of Semantic Relation Composition
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2011
Authors

This paper presents an unsupervised method for deriving inference axioms by composing semantic relations. The method is indepen- dent 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 eval- uated over PropBank.