Relation Extraction as Contextualized Sequence Classification

An example of relation extraction from wetlab protocols.

Abstract

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.

Publication
Proceedings of the Sixth Workshop on Noisy User-generated Text (W-NUT 2020)

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Chris Miller
Chris Miller
Software Engineer & Incoming PhD Student

I’m a software developer at Microsoft working on Azure services, and an incoming PhD student at USC Viterbi.