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Joint Entity And Relation Extraction On

평가 지표

Cross Sentence
Entity F1

평가 결과

이 벤치마크에서 각 모델의 성능 결과

모델 이름
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-
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Joint Entity And Relation Extraction On | SOTA | HyperAI초신경