Binary classification model as a tool to detect sentences with microsyntactic units
Alexandra Chaga · Computational Linguistics and Intellectual Technologies · 2023
We consider a model of binary classifier predicting occurrence of microsyntactic units in sentences. The model is based on AWD-LSTM architecture with an encoder pre-trained on the Russian version of Wikipedia and further trained on a dataset built from the SynTagRus corpus supplied with a microsyntactic markup. We present the structure of the model and discuss its output. The study showed that binary classification allows targeting of microsyntactic markup and helps to significantly improve its recall.