Relation Extraction On Webnlg

Results

Performance results of various models on this benchmark

		Paper Title
UniRel	94.7	UniRel: Unified Representation and Interaction for Joint Relational Triple Extraction
PFN	93.6	A Partition Filter Network for Joint Entity and Relation Extraction
SPN	93.4	Joint Entity and Relation Extraction with Set Prediction Networks
TDEER	93.1	TDEER: An Efficient Translating Decoding Schema for Joint Extraction of Entities and Relations
RIFRE	92.6	Representation Iterative Fusion based on Heterogeneous Graph Neural Network for Joint Entity and Relation Extraction
TPLinker	91.9	TPLinker: Single-stage Joint Extraction of Entities and Relations Through Token Pair Linking
HBT (CasRel)	91.8	A Novel Cascade Binary Tagging Framework for Relational Triple Extraction
RIN (BERT, K=2)	90.1	Recurrent Interaction Network for Jointly Extracting Entities and Classifying Relations
CGT(UniLM)	83.4	Contrastive Triple Extraction with Generative Transformer
ETL-Span	83.1	Joint Extraction of Entities and Relations Based on a Novel Decomposition Strategy
RSAN	82.1	A Relation-Specific Attention Network for Joint Entity and Relation Extraction
CopyRE' OneDecoder	60.5	CopyMTL: Copy Mechanism for Joint Extraction of Entities and Relations with Multi-Task Learning
CopyRE MultiDecoder	37.1	Extracting Relational Facts by an End-to-End Neural Model with Copy Mechanism
NovelTagging	28.3	Joint Extraction of Entities and Relations Based on a Novel Tagging Scheme

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