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Joint Entity And Relation Extraction On

Métriques

Cross Sentence
Entity F1

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle
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 | HyperAI