  We present RuDSI, a new benchmark for word sense induction (WSI) in Russian.
The dataset was created using manual annotation and semi-automatic clustering
of Word Usage Graphs (WUGs). Unlike prior WSI datasets for Russian, RuDSI is
completely data-driven (based on texts from Russian National Corpus), with no
external word senses imposed on annotators. Depending on the parameters of
graph clustering, different derivative datasets can be produced from raw
annotation. We report the performance that several baseline WSI methods obtain
on RuDSI and discuss possibilities for improving these scores.
