Recognizing Implied Predicate-Argument Relationships in Textual Inference

We investigate recognizing implied predicate-argument relationships which are not explicitly expressed in syntactic structure. While prior works addressed such relationships as an extension to semantic role labeling, our work investigates them in the context of textual inference scenarios. Such scenarios provide prior information, which substantially eases the task. We provide a large and freely available evaluation dataset for our task setting, and propose methods to cope with it, while obtaining promising results in empirical evaluations.