In this paper, we bridge the gap between distributional and frame semantics by linking distributional semantic representations to Framester, a knowledge graph that acts as a hub between resources like FrameNet, BabelNet and DBpedia, among others.
of this, we introduce a new lexical resource that enriches the Framester knowledge graph with distributional features extracted from text, and show how this hybrid resource yields better results on the task of recognizing frames in running text.