  We introduce a new lexical resource that enriches the Framester knowledge
graph, which links Framnet, WordNet, VerbNet and other resources, with semantic
features from text corpora. These features are extracted from distributionally
induced sense inventories and subsequently linked to the manually-constructed
frame representations to boost the performance of frame disambiguation in
context. Since Framester is a frame-based knowledge graph, which enables
full-fledged OWL querying and reasoning, our resource paves the way for the
development of novel, deeper semantic-aware applications that could benefit
from the combination of knowledge from text and complex symbolic
representations of events and participants. Together with the resource we also
provide the software we developed for the evaluation in the task of Word Frame
Disambiguation (WFD).
