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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 21–30 of 87 papers

TitleStatusHype
Generalizing through Forgetting -- Domain Generalization for Symptom Event Extraction in Clinical Notes—0
A Two-Phase Paradigm for Joint Entity-Relation Extraction—0
EmRel: Joint Representation of Entities and Embedded Relations for Multi-triple ExtractionCode0
JBNU-CCLab at SemEval-2022 Task 12: Machine Reading Comprehension and Span Pair Classification for Linking Mathematical Symbols to Their DescriptionsCode0
AIFB-WebScience at SemEval-2022 Task 12: Relation Extraction First - Using Relation Extraction to Identify EntitiesCode0
REKnow: Enhanced Knowledge for Joint Entity and Relation Extraction—0
SciDeBERTa: Learning DeBERTa for Science Technology Documents and Fine-Tuning Information Extraction TasksCode0
STable: Table Generation Framework for Encoder-Decoder Models—0
DeepStruct: Pretraining of Language Models for Structure PredictionCode1
Modeling Task Interactions in Document-Level Joint Entity and Relation Extraction—0
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