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Joint Entity and Relation Extraction

Joint Entity and Relation Extraction is the task of extracting entity mentions and semantic relations between entities from unstructured text with a single model.

Papers

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Showing 51–60 of 87 papers

TitleStatusHype
EmRel: Joint Representation of Entities and Embedded Relations for Multi-triple Extraction—0
Enhancing Knowledge Graph Construction Using Large Language Models—0
OneRel:Joint Entity and Relation Extraction with One Module in One Step—0
Entity Relative Position Representation based Multi-head Selection for Joint Entity and Relation Extraction—0
Extracting Fine-Grained Knowledge Graphs of Scientific Claims: Dataset and Transformer-Based Results—0
Generalizing through Forgetting -- Domain Generalization for Symptom Event Extraction in Clinical Notes—0
GenerativeRE: Incorporating a Novel Copy Mechanism and Pretrained Model for Joint Entity and Relation Extraction—0
Span-based Joint Entity and Relation Extraction with Attention-based Span-specific and Contextual Semantic Representations—0
Improved Decomposition Strategy for Joint Entity and Relation Extraction—0
Query-based Instance Discrimination Network for Relational Triple Extraction—0
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