HyperAIHyperAI超神经
首页资讯最新论文教程数据集百科SOTALLM 模型天梯GPU 天梯顶会
全站搜索
关于
HyperAIHyperAI超神经

Joint Entity And Relation Extraction On

评估指标

Cross Sentence
Entity F1

评测结果

各个模型在此基准测试上的表现结果

模型名称
Cross Sentence
Entity F1
Paper TitleRepository
SpERTNo70.33Span-based Joint Entity and Relation Extraction with Transformer Pre-training-
TriMF-70.17A Trigger-Sense Memory Flow Framework for Joint Entity and Relation Extraction-
SciIENo64.20Multi-Task Identification of Entities, Relations, and Coreference for Scientific Knowledge Graph Construction-
PL-MarkerYes69.9Packed Levitated Marker for Entity and Relation Extraction-
SpERT.PL (SciBERT)No70.53Joint Entity and Relation Extraction from Scientific Documents: Role of Linguistic Information and Entity Types
DyGIEYes65.2A General Framework for Information Extraction using Dynamic Span Graphs-
MGENo68.4A Multi-Gate Encoder for Joint Entity and Relation Extraction-
PFNNo66.8A Partition Filter Network for Joint Entity and Relation Extraction-
Ours: cross-sentenceYes68.9A Frustratingly Easy Approach for Entity and Relation Extraction-
SpERT (with overlap)No70.3Span-based Joint Entity and Relation Extraction with Transformer Pre-training-
DyGIE++Yes67.50Entity, Relation, and Event Extraction with Contextualized Span Representations-
0 of 11 row(s) selected.