  We present RuSemShift, a large-scale manually annotated test set for the task
of semantic change modeling in Russian for two long-term time period pairs:
from the pre-Soviet through the Soviet times and from the Soviet through the
post-Soviet times. Target words were annotated by multiple crowd-source
workers. The annotation process was organized following the DURel framework and
was based on sentence contexts extracted from the Russian National Corpus.
Additionally, we report the performance of several distributional approaches on
RuSemShift, achieving promising results, which at the same time leave room for
other researchers to improve.
