Turnaev A.., Apanovich Z..pdf287.45 KB

This paper describes a pipeline for extracting the author’s terms and definitions from mathematical texts. We used two models: one, for detecting mathematical formulas to clear text from noise and the other, for converting images into LaTeX formulas to restore the deleted formulas. Experimental data show that noise clearing is...

Article _1_Bul_45_.pdf1023.8 KB

This paper describes the experiments for the task on information extraction from news texts in Russian in a setting with a wide variety of types of entities and relations. We have adapted the SpERT model which uses the BERT network as a core for the joint extraction of entities and...