Relation Extraction On Tacred

评估指标

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	Repository
DeepStruct multi-task w/ finetune	76.8	DeepStruct: Pretraining of Language Models for Structure Prediction	-
TRE	67.4	Improving Relation Extraction by Pre-trained Language Representations	-
SA-LSTM+D	67.6	Beyond Word Attention: Using Segment Attention in Neural Relation Extraction	-
C-AGGCN	68.2	Attention Guided Graph Convolutional Networks for Relation Extraction	-
LUKE	-	LUKE: Deep Contextualized Entity Representations with Entity-aware Self-attention	-
K-ADAPTER (F+L)	72.04	K-Adapter: Infusing Knowledge into Pre-Trained Models with Adapters	-
C-GCN	66.4	Graph Convolution over Pruned Dependency Trees Improves Relation Extraction	-
RoBERTa-large-typed-marker	74.6	An Improved Baseline for Sentence-level Relation Extraction	-
C-GCN + PA-LSTM	68.2	Graph Convolution over Pruned Dependency Trees Improves Relation Extraction	-
KEPLER	71.7	KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation	-
AGGCN	65.1	Attention Guided Graph Convolutional Networks for Relation Extraction	-
RE-MC	75.4	Enhancing Targeted Minority Class Prediction in Sentence-Level Relation Extraction
ERNIE	67.97	ERNIE: Enhanced Language Representation with Informative Entities	-
C-SGC	67.0	Simplifying Graph Convolutional Networks	-
RECENT+SpanBERT	75.2	Relation Classification with Entity Type Restriction	-
SpanBERT-large	70.8	SpanBERT: Improving Pre-training by Representing and Predicting Spans	-
NLI_RoBERTa	71.0	Label Verbalization and Entailment for Effective Zero- and Few-Shot Relation Extraction	-
KnowBert-W+W	71.5	Knowledge Enhanced Contextual Word Representations	-
LLM-QA4RE (XXLarge)	52.2	Aligning Instruction Tasks Unlocks Large Language Models as Zero-Shot Relation Extractors	-
Contrastive Pre-training	69.5	Learning from Context or Names? An Empirical Study on Neural Relation Extraction	-

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