TASK	DATASET	MODEL	METRIC NAME	METRIC VALUE	GLOBAL RANK
Relation Extraction	WNUT 2020	Baseline	Precision	80.1	# 1
Relation Extraction	WNUT 2020	Baseline	Recall	66.21	# 1
Relation Extraction	WNUT 2020	Baseline	F1	72.5	# 1
Named Entity Recognition (NER)	WNUT 2020	Baseline	Precision	70.06	# 1
Named Entity Recognition (NER)	WNUT 2020	Baseline	Recall	61.91	# 1
Named Entity Recognition (NER)	WNUT 2020	Baseline	F1	65.73	# 3

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WNUT-2020 Task 1 Overview: Extracting Entities and Relations from Wet Lab Protocols

EMNLP (WNUT) 2020 · Jeniya Tabassum, Sydney Lee, Wei Xu, Alan Ritter ·

This paper presents the results of the wet lab information extraction task at WNUT 2020. This task consisted of two sub tasks: (1) a Named Entity Recognition (NER) task with 13 participants and (2) a Relation Extraction (RE) task with 2 participants. We outline the task, data annotation process, corpus statistics, and provide a high-level overview of the participating systems for each sub task.

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named-entity-recognition

Named Entity Recognition

Named Entity Recognition (NER)

NER

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Relation Extraction

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WNUT 2020

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Task	Dataset	Model	Metric Name	Metric Value	Global Rank	Benchmark
Relation Extraction	WNUT 2020	Baseline	Precision	80.1	# 1	Compare
			Recall	66.21	# 1	Compare
			F1	72.5	# 1	Compare
Named Entity Recognition (NER)	WNUT 2020	Baseline	Precision	70.06	# 1	Compare
			Recall	61.91	# 1	Compare
			F1	65.73	# 3	Compare

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