Big Green at WNUT 2020 Shared Task-1: Relation Extraction as Contextualized Sequence Classification
This work addresses the problem of extracting relations and events from noisy text for researchers working with wet lab protocols, representing an incremental improvement in this domain.
This paper tackles relation and event extraction from noisy text, specifically wet lab protocols. The system uses contextualized knowledge graph completion to classify relations and events between known entities, demonstrating effective extraction from the dataset.
Relation and event extraction is an important task in natural language processing. We introduce a system which uses contextualized knowledge graph completion to classify relations and events between known entities in a noisy text environment. We report results which show that our system is able to effectively extract relations and events from a dataset of wet lab protocols.