  This paper is devoted to the extraction of entities and semantic relations
between them from scientific texts, where we consider scientific terms as
entities. In this paper, we present a dataset that includes annotations for two
tasks and develop a system called TERMinator for the study of the influence of
language models on term recognition and comparison of different approaches for
relation extraction. Experiments show that language models pre-trained on the
target language are not always show the best performance. Also adding some
heuristic approaches may improve the overall quality of the particular task.
The developed tool and the annotated corpus are publicly available at
https://github.com/iis-research-team/terminator and may be useful for other
researchers.
