Relation Extraction On Nyt

评测结果

各个模型在此基准测试上的表现结果

模型名称	F1	Paper Title
DIRECT	92.5	Adjacency List Oriented Relational Fact Extraction via Adaptive Multi-task Learning
SPN	92.5	Joint Entity and Relation Extraction with Set Prediction Networks
ReLiK-Base	94.8	ReLiK: Retrieve and LinK, Fast and Accurate Entity Linking and Relation Extraction on an Academic Budget
ReLiK-Large	95	ReLiK: Retrieve and LinK, Fast and Accurate Entity Linking and Relation Extraction on an Academic Budget
REBEL (no pre-training)	93.1	REBEL: Relation Extraction By End-to-end Language generation
ReLiK-Small	94.4	ReLiK: Retrieve and LinK, Fast and Accurate Entity Linking and Relation Extraction on an Academic Budget
TDEER	92.5	TDEER: An Efficient Translating Decoding Schema for Joint Extraction of Entities and Relations
UniRel	93.7	UniRel: Unified Representation and Interaction for Joint Relational Triple Extraction

0 of 8 row(s) selected.