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2020 EMNLP EMNLP 2020

Big Green at WNUT 2020 Shared Task-1: Relation Extraction as Contextualized Sequence Classification

Abstract

AbstractRelation 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.

🌉 Interdisciplinary Bridge - Artificial Intelligence and Knowledge & Reasoning and Natural Language Processing

Authors

Chris Miller, Soroush Vosoughi

Topics

Machine Learning > Core Methods > Classification Natural Language Processing > Applications > Information Extraction Knowledge & Reasoning > Representation > Knowledge Graphs Deep Learning > Learning Types > Classification Natural Language Processing > Applications > Relation Extraction

Keywords

text classification relation extraction sequence classification knowledge graph knowledge graph completion event extraction wet lab protocol
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