Detection of semantic changes in Russian nouns with distributional models and grammatical features
The paper presents the models detecting the degree of semantic change in Russian nouns developed by the team
aryzhova within the RuShiftEval competition of the Dialogue 2021 conference. We base our algorithms mostly
on unsupervised distributional models and additionally test a model that uses vectors representing morphological
preferences of the words in question. The best results are obtained by the model built on the ELMo architecture
with a small window, while the quality of performance of the “grammatical” model is comparable to that of the
models based on much more sophisticated algorithms.