Although researchers have shown increasing interest in extracting/classifying semantic relations, most previous studies have basically relied on lexical patterns between terms. This paper proposes a novel way to accomplish the task: a system that captures a physical size of an entity. Experimental results revealed that our proposed method is feasible and prevents the problems inherent in other methods.
REF focused on the physical size of an entity to predict the semantic relation between entities.
UTH: SVM-based Semantic Relation Classification using Physical Sizes
Fourth International Workshop on Semantic Evaluations (SemEval-2007)
Computer Science