RENERSANs: Relation Extraction and Named Entity Recognition as Sequence Annotation
In this work we present our system for RuREBus shared task held together with Dialog 2020 conference. The task consisted of 3 subtasks: named entity recognition, relation extraction with provided named entity tags and end-to-end relation extraction. Our system took the first and the second place in the first and the second subtasks respectively. For the third subtask we submitted our solution only in the post-evaluation phase, however, it was among the top 2 best performing systems. The systems for all tasks are based on Transformer models. Relation extraction was solved as a sequence labelling problem. We also used joint task named entity and relation extraction learning.