Binary Relation Extraction
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Benchmarks
Most implemented
BioRED: A Rich Biomedical Relation Extraction Dataset
Multi-Attribute Relation Extraction (MARE) -- Simplifying the Application of Relation Extraction
Document-level Entity-based Extraction as Template Generation
Papers
BioRED: A Rich Biomedical Relation Extraction Dataset
Automated relation extraction (RE) from biomedical literature is critical for many downstream text mining applications in both research and real-world settings. However, most existing benchmarking datasets for bio-medica…
BenchmarkingBinary Relation ExtractionNamed Entity RecognitionNamed Entity Recognition (NER)+3Multi-Attribute Relation Extraction (MARE) -- Simplifying the Application of Relation Extraction
Natural language understanding's relation extraction makes innovative and encouraging novel business concepts possible and facilitates new digitilized decision-making processes. Current approaches allow the extraction of…
AttributeBinary Relation ExtractionDecision MakingEvent Extraction+2Document-level Entity-based Extraction as Template Generation
Document-level entity-based extraction (EE), aiming at extracting entity-centric information such as entity roles and entity relations, is key to automatic knowledge acquisition from text corpora for various domains. Mos…
4-ary Relation ExtractionBinary Relation ExtractionRole-filler Entity ExtractionBERT-GT: Cross-sentence n-ary relation extraction with BERT and Graph Transformer
A biomedical relation statement is commonly expressed in multiple sentences and consists of many concepts, including gene, disease, chemical, and mutation. To automatically extract information from biomedical literature,…
BenchmarkingBinary Relation ExtractionGraph Neural NetworkRelation+2Complex Relation Extraction: Challenges and Opportunities
Relation extraction aims to identify the target relations of entities in texts. Relation extraction is very important for knowledge base construction and text understanding. Traditional binary relation extraction, includ…
Binary Relation ExtractionKnowledge Base ConstructionRelationRelation ExtractionYNU-junyi in BioNLP-OST 2019: Using CNN-LSTM Model with Embeddings for SeeDev Binary Event Extraction
We participated in the BioNLP 2019 Open Shared Tasks: binary relation extraction of SeeDev task. The model was constructed us- ing convolutional neural networks (CNN) and long short term memory networks (LSTM). The full …
Binary Relation ExtractionEvent ExtractionRelationRelation Extraction