Document-level Relation Extraction
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Benchmarks
Most implemented
DocRED: A Large-Scale Document-Level Relation Extraction Dataset
Revisiting DocRED -- Addressing the False Negative Problem in Relation Extraction
Entity Structure Within and Throughout: Modeling Mention Dependencies for Document-Level Relation Extraction
Rethinking the Role of LLMs for Document-level Relation Extraction: a Refiner with Task Distribution and Probability Fusion
AutoRE: Document-Level Relation Extraction with Large Language Models
Papers
Ontology-Driven Structural Regularization for Document-Level Relation Extraction
Document-Level Relation Extraction (DocRE) relies heavily on costly manually annotated datasets, while large distant supervision resources such as DocRED distant remain underexploited due to noise. We show that a critica…
Document-level Relation ExtractionA Domain-Specific Curated Benchmark for Entity and Document-Level Relation Extraction
Information Extraction (IE), encompassing Named Entity Recognition (NER), Named Entity Linking (NEL), and Relation Extraction (RE), is critical for transforming the rapidly growing volume of scientific publications into …
Document-level Relation ExtractionInformation ExtractionEntity LinkingDOREMI: Optimizing Long Tail Predictions in Document-Level Relation Extraction
Document-Level Relation Extraction (DocRE) presents significant challenges due to its reliance on cross-sentence context and the long-tail distribution of relation types, where many relations have scarce training example…
Document-level Relation ExtractionRelation as a Prior: A Novel Paradigm for LLM-based Document-level Relation Extraction
Large Language Models (LLMs) have demonstrated their remarkable capabilities in document understanding. However, recent research reveals that LLMs still exhibit performance gaps in Document-level Relation Extraction (Doc…
Document-level Relation ExtractionGLiDRE: Generalist Lightweight model for Document-level Relation Extraction
Relation Extraction (RE) is a fundamental task in Natural Language Processing, and its document-level variant poses significant challenges, due to complex interactions between entities across sentences. While supervised …
Document-level Relation ExtractionMulti-Relation Extraction in Entity Pairs using Global Context
In document-level relation extraction, entities may appear multiple times in a document, and their relationships can shift from one context to another. Accurate prediction of the relationship between two entities across …
Document-level Relation Extraction