SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1–10 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
REXEL: An End-to-end Model for Document-Level Relation Extraction and Entity LinkingCode1
EnriCo: Enriched Representation and Globally Constrained Inference for Entity and Relation ExtractionCode1
Joint Entity and Relation Extraction with Span Pruning and Hypergraph Neural NetworksCode1
DocRED-FE: A Document-Level Fine-Grained Entity And Relation Extraction DatasetCode1
Knowledge Graph Generation From TextCode1
KPI-EDGAR: A Novel Dataset and Accompanying Metric for Relation Extraction from Financial DocumentsCode1
DeepStruct: Pretraining of Language Models for Structure PredictionCode1
Joint Entity and Relation Extraction Based on Table Labeling Using Convolutional Neural NetworksCode1
Show:102550
← PrevPage 1 of 9Next →

No leaderboard results yet.