Relation Extraction on CoNLL04

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RE+ Macro F1

Rank	Model	RE+ Macro F1	RE+ Micro F1	NER Macro F1	NER Micro F1	Extra Training Data	Paper	Code	Year
1	REBEL	76.65	75.4	–	–	✓	REBEL: Relation Extraction By End-to-end Language generation	Babelscape/rebel	2021
2	Table-Sequence	75.4	73.6	86.9	90.1		Two are Better than One: Joint Entity and Relation Extraction with Table-Sequence Encoders	LorrinWWW/two-are-better-than-one · saarahasad/Relation-Extraction	2020
3	SpERT	72.87	71.47	86.25	88.94		Span-based Joint Entity and Relation Extraction with Transformer Pre-training	markus-eberts/spert · lavis-nlp/spert · yangyucheng000/Paper-3	2019
4	Deeper	72.63	71.08	87	89.78		Deeper Task-Specificity Improves Joint Entity and Relation Extraction	vedantc6/mtl-dts	2020
5	Biaffine attention	64.4	–	86.2	–		End-to-end neural relation extraction using deep biaffine attention	datquocnguyen/jointRE	2018
6	Relation-Metric with AT	62.29	–	84.15	–		Neural Metric Learning for Fast End-to-End Relation Extraction		2019
7	multi-head	62.04	–	83.9	–		Joint entity recognition and relation extraction as a multi-head selection problem	bekou/multihead_joint_entity_relation_extraction · mangonihao/MultiHeadJointEntityRelationExtraction_simple · WindChimeRan/OpenJERE · +3	2018
8	multi-head + AT	61.95	–	83.6	–		Adversarial training for multi-context joint entity and relation extraction	bekou/multihead_joint_entity_relation_extraction	2018
9	ReLiK-Large	–	78.1	–	–		ReLiK: Retrieve and LinK, Fast and Accurate Entity Linking and Relation Extraction on an Academic Budget	SapienzaNLP/relik · RadeenXALNW/G-RAG_1.0	2024
10	ASP+T0-3B	–	76.3	–	90.3		Autoregressive Structured Prediction with Language Models	lyutyuh/asp	2022
11	TablERT	–	72.6	–	90.2		Named Entity Recognition and Relation Extraction using Enhanced Table Filling by Contextualized Representations	YoumiMa/TablERT	2020
12	TANL	–	72.6	–	–		Structured Prediction as Translation between Augmented Natural Languages	amazon-science/tanl · amazon-research/tanl	2021
13	TriMF	–	72.35	–	90.3		A Trigger-Sense Memory Flow Framework for Joint Entity and Relation Extraction	tricktreat/trimf	2021
14	Multi-turn QA	–	68.9	–	87.8		Entity-Relation Extraction as Multi-Turn Question Answering	ShannonAI/Entity-Relation-As-Multi-Turn-QA	2019
15	Global	–	67.8	–	85.6		End-to-End Neural Relation Extraction with Global Optimization		2017
16	Table Representation	–	61	–	80.7		Modeling Joint Entity and Relation Extraction with Table Representation		2014