Relation Extraction On Nyt11 Hrl

Results

Performance results of various models on this benchmark

Model Name	F1	Paper Title
TPLinker	55.67	TPLinker: Single-stage Joint Extraction of Entities and Relations Through Token Pair Linking
NovelTagging	47.9	Joint Extraction of Entities and Relations Based on a Novel Tagging Scheme
CopyR	42.1	Extracting Relational Facts by an End-to-End Neural Model with Copy Mechanism
HRL	53.8	Revisiting the Negative Data of Distantly Supervised Relation Extraction
CasRel (exact)	51.25	A Novel Cascade Binary Tagging Framework for Relational Triple Extraction
ReRe (exact)	55.47	Revisiting the Negative Data of Distantly Supervised Relation Extraction
TPLinker	55.28	TPLinker: Single-stage Joint Extraction of Entities and Relations Through Token Pair Linking
CasRel	53.9	A Novel Cascade Binary Tagging Framework for Relational Triple Extraction
SPTree	53.1	End-to-End Relation Extraction using LSTMs on Sequences and Tree Structures
HRL	53.8	A Hierarchical Framework for Relation Extraction with Reinforcement Learning
RERE	56.23	Revisiting the Negative Data of Distantly Supervised Relation Extraction
Cotype	43	CoType: Joint Extraction of Typed Entities and Relations with Knowledge Bases

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