ИСТИНА

We propose a realization of sequence labeling approach to grammatical error correction of Russian. We discuss the difficulties of method adaptation and the modifications we made in order to deal with Russian morphology. Our model outperforms SOTA single model approaches on GERA corpus, achieving the F0.5 score of 69.9%, and shows solid performance on other corpora as well.