Augmenting a Semantic Verb Lexicon with a Large Scale Collection of Example Sentences

Abstract

In this paper, we propose a method of reducing the cost of annotating examples with argument structure in order to increase accuracy of argument structure analysis.First, a large raw corpus is parsed, and a large scale collection of example sentences is constructed from predicate-argument examples in the parsing results.Second, the collection of example sentences is clustered by using two similarities about verb.Finally, the acquired clusters are annotated with argument structure by human.We report preliminary experiments using our proposed method, and show that the method is effective in reducing the cost of annotating.