A Step-wise Usage-based Method for Inducing Polysemy-aware Verb Classes

We present an unsupervised method for in-ducing verb classes from verb uses in giga-word corpora. Our method consists of two clustering steps: verb-specific seman-tic frames are first induced by clustering verb uses in a corpus and then verb classes are induced by clustering these frames. By taking this step-wise approach, we can not only generate verb classes based on a massive amount of verb uses in a scalable manner, but also deal with verb polysemy, which is bypassed by most of the previous studies on verb clustering. In our exper-iments, we acquire semantic frames and verb classes from two giga-word corpora, the larger comprising 20 billion words. The effectiveness of our approach is veri-fied through quantitative evaluations based on polysemy-aware gold-standard data.