Dependency Parsing of Natural Russian Language with Usage of Semantic Mapping Approach

This article discusses the practical implementation of a linguistic processor that solves the task of parsing dependencies. Within this paper, we investigated various modern developments on the ability to adequately parse natural language sentences in Russian. As a result, we suggest the new method of dependency parsing based on BiLSTM neural networks. The comparative analysis showed that suggested method shows the best results than other parsers. We are going to improve our algorithm by appending the semantic analysis with the usage of semantic mapping for better understanding the intentions of sentences.