  Recently many studies have been conducted on the topic of relation
extraction. The DrugProt track at BioCreative VII provides a manually-annotated
corpus for the purpose of the development and evaluation of relation extraction
systems, in which interactions between chemicals and genes are studied. We
describe the ensemble system that we used for our submission, which combines
predictions of fine-tuned bioBERT, sciBERT and const-bioBERT models by majority
voting. We specifically tested the contribution of syntactic information to
relation extraction with BERT. We observed that adding constituentbased
syntactic information to BERT improved precision, but decreased recall, since
relations rarely seen in the train set were less likely to be predicted by BERT
models in which the syntactic information is infused. Our code is available
online [https://github.com/Maple177/drugprot-relation-extraction].
