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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 1–25 of 87 papers

TitleStatusHype
GraphER: A Structure-aware Text-to-Graph Model for Entity and Relation ExtractionCode2
An Autoregressive Text-to-Graph Framework for Joint Entity and Relation ExtractionCode2
Joint Entity and Relation Extraction from Scientific Documents: Role of Linguistic Information and Entity TypesCode1
Extracting Fine-Grained Knowledge Graphs of Scientific Claims: Dataset and Transformer-Based ResultsCode1
HySPA: Hybrid Span Generation for Scalable Text-to-Graph ExtractionCode1
Joint Entity and Relation Extraction Based on Table Labeling Using Convolutional Neural NetworksCode1
EnriCo: Enriched Representation and Globally Constrained Inference for Entity and Relation ExtractionCode1
A General Framework for Information Extraction using Dynamic Span GraphsCode1
A Partition Filter Network for Joint Entity and Relation ExtractionCode1
A Relation-Specific Attention Network for Joint Entity and Relation ExtractionCode1
Effective Modeling of Encoder-Decoder Architecture for Joint Entity and Relation ExtractionCode1
A Trigger-Sense Memory Flow Framework for Joint Entity and Relation ExtractionCode1
Injecting Knowledge Base Information into End-to-End Joint Entity and Relation Extraction and Coreference ResolutionCode1
Joint Biomedical Entity and Relation Extraction with Knowledge-Enhanced Collective InferenceCode1
DocRED-FE: A Document-Level Fine-Grained Entity And Relation Extraction DatasetCode1
Entity, Relation, and Event Extraction with Contextualized Span RepresentationsCode1
An End-to-end Model for Entity-level Relation Extraction using Multi-instance LearningCode1
A Cascade Dual-Decoder Model for Joint Entity and Relation ExtractionCode1
CoType: Joint Extraction of Typed Entities and Relations with Knowledge BasesCode1
Deeper Task-Specificity Improves Joint Entity and Relation ExtractionCode1
Deep Neural Networks for Relation ExtractionCode1
DeepStruct: Pretraining of Language Models for Structure PredictionCode1
A sequence-to-sequence approach for document-level relation extractionCode1
A Frustratingly Easy Approach for Entity and Relation ExtractionCode1
Joint Entity and Relation Extraction with Span Pruning and Hypergraph Neural NetworksCode1
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