New Dataset and Strong Baselines for the Grammatical Error Correction of Russian

Motivated by recent advancements in grammatical error correction in English and existing issues in the field, we describe a new resource, an annotated learner corpus of Russian, extracted from the Lang-8 language learning website. This new dataset is benchmarked against two grammatical error correction models that use state-of-the-art neural architectures. Results are provided on the newlycreated corpus and are compared against performance on another, existing resource. We also evaluate the contribution of the Lang-8 training data to the grammatical error correction of Russian and perform type-based analysis of the models. The expert annotations are available for research purposes.