SOTAVerified

Relation Extraction

Relation Extraction is the task of predicting attributes and relations for entities in a sentence. For example, given a sentence “Barack Obama was born in Honolulu, Hawaii.”, a relation classifier aims at predicting the relation of “bornInCity”. Relation Extraction is the key component for building relation knowledge graphs, and it is of crucial significance to natural language processing applications such as structured search, sentiment analysis, question answering, and summarization.

Source: Deep Residual Learning for Weakly-Supervised Relation Extraction

Papers

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Showing 1001–1050 of 1977 papers

TitleStatusHype
Domain adaptation in practice: Lessons from a real-world information extraction pipeline—0
Is ``hot pizza'' Positive or Negative? Mining Target-aware Sentiment Lexicons—0
Dynamic Graph Transformer for Implicit Tag Recognition—0
Normal vs. Adversarial: Salience-based Analysis of Adversarial Samples for Relation ExtractionCode0
Deep Neural Approaches to Relation Triplets Extraction: A Comprehensive Survey—0
Multi-facet Universal Schema—0
Structural block driven - enhanced convolutional neural representation for relation extraction—0
Leveraging Unlabeled Data for Entity-Relation Extraction through Probabilistic Constraint Satisfaction—0
Cross-Task Instance Representation Interactions and Label Dependencies for Joint Information Extraction with Graph Convolutional Networks—0
Mention-centered Graph Neural Network for Document-level Relation Extraction—0
A Review on Semi-Supervised Relation Extraction—0
Techniques for Jointly Extracting Entities and Relations: A Survey—0
Dual Pointer Network for Fast Extraction of Multiple Relations in a Sentence—0
Better Call the Plumber: Orchestrating Dynamic Information Extraction Pipelines—0
REMOD: Relation Extraction for Modeling Online DiscourseCode0
Contextual Argument Component Classification for Class Discussions—0
Jointly Learning Clinical Entities and Relations with Contextual Language Models and Explicit Context—0
Two Training Strategies for Improving Relation Extraction over Universal GraphCode0
TINKER: A framework for Open source Cyberthreat Intelligence—0
Memorization vs. Generalization: Quantifying Data Leakage in NLP Performance EvaluationCode0
Neural Data Augmentation via Example ExtrapolationCode0
"Is depression related to cannabis?": A knowledge-infused model for Entity and Relation Extraction with Limited Supervision—0
LOME: Large Ontology Multilingual Extraction—0
Process-Level Representation of Scientific Protocols with Interactive AnnotationCode0
HIVE-4-MAT: Advancing the Ontology Infrastructure for Materials Science—0
A Survey on Extraction of Causal Relations from Natural Language Text—0
BERT-GT: Cross-sentence n-ary relation extraction with BERT and Graph Transformer—0
Learning Better Sentence Representation with Syntax Information—0
Deep Neural Network Based Relation Extraction: An Overview—0
Discourse-level Relation Extraction via Graph Pooling—0
An Automated Domain Understanding Technique for Knowledge Graph Generation—0
Counterfactual Thinking for Long-tailed Information Extraction—0
LayoutLMv2: Multi-modal Pre-training for Visually-Rich Document UnderstandingCode0
BERTChem-DDI : Improved Drug-Drug Interaction Prediction from text using Chemical Structure Information—0
A hybrid deep-learning approach for complex biochemical named entity recognition—0
An Empirical Study of Using Pre-trained BERT Models for Vietnamese Relation Extraction Task at VLSP 2020Code0
Regularized Attentive Capsule Network for Overlapped Relation Extraction—0
InSRL: A Multi-view Learning Framework Fusing Multiple Information Sources for Distantly-supervised Relation Extraction—0
Complex Relation Extraction: Challenges and Opportunities—0
Improving Relation Extraction by Leveraging Knowledge Graph Link PredictionCode0
From Bag of Sentences to Document: Distantly Supervised Relation Extraction via Machine Reading ComprehensionCode0
Big Green at WNUT 2020 Shared Task-1: Relation Extraction as Contextualized Sequence Classification—0
H-FND: Hierarchical False-Negative Denoising for Distant Supervision Relation ExtractionCode0
Event Guided Denoising for Multilingual Relation Learning—0
Financial Document Causality Detection Shared Task (FinCausal 2020)—0
Coarse-to-Fine Entity Representations for Document-level Relation ExtractionCode0
Automatic Extraction of Ranked SNP-Phenotype Associations from Literature through Detecting Neural Candidates, Negation and Modality Markers—0
Span-based Joint Entity and Relation Extraction with Attention-based Span-specific and Contextual Semantic Representations—0
Global Context-enhanced Graph Convolutional Networks for Document-level Relation ExtractionCode0
Joint Entity and Relation Extraction for Legal Documents with Legal Feature Enhancement—0
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All datasetsDocREDTACREDSemEval-2010 Task-8ACE 2005CoNLL04Adverse Drug Events (ADE) CorpusWebNLGChemProtACE 2004NYT11-HRLCDRGDA

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DREEAMF167.53—Unverified
2KD-Rb-lF167.28—Unverified
3SSAN-RoBERTa-large+AdaptationF165.92—Unverified
4SAIS-RoBERTa-largeF165.11—Unverified
5Eider-RoBERTa-largeF164.79—Unverified
6DocuNet-RoBERTa-largeF164.55—Unverified
7CGM2IR-RoBERTalargeF163.89—Unverified
8SETE-Roberta-largeF163.74—Unverified
9ATLOP-RoBERTa-largeF163.4—Unverified
10DRE-MIR-BERTbaseF163.15—Unverified
#ModelMetricClaimedVerifiedStatus
1RAG4REF186.6—Unverified
2DeepStruct multi-task w/ finetuneF176.8—Unverified
3UNiST (LARGE)F175.5—Unverified
4RE-MCF175.4—Unverified
5GenPT (T5)F175.3—Unverified
6RECENT+SpanBERTF175.2—Unverified
7SuRE (PEGASUS-large)F175.1—Unverified
8EXOBRAINF175—Unverified
9Relation ReductionF174.8—Unverified
10RoBERTa-large-typed-markerF174.6—Unverified
#ModelMetricClaimedVerifiedStatus
1SPF191.9—Unverified
2RIFREF191.3—Unverified
3REDNF191—Unverified
4SPOTF190.6—Unverified
5KLGF190.5—Unverified
6RELAF190.4—Unverified
7Skeleton-Aware BERTF190.36—Unverified
8LUKEF190.3—Unverified
9KnowPromptF190.3—Unverified
10EPGNNF190.2—Unverified
#ModelMetricClaimedVerifiedStatus
1Span-levelNER Micro F185.98—Unverified
2Dual Pointer Network(multi-head)Relation classification F180.8—Unverified
3Dual Pointer NetworkRelation classification F180.5—Unverified
4PL-MarkerRE Micro F173—Unverified
5ASP+T5-3BRE Micro F172.7—Unverified
6GoLLIERE Micro F170.1—Unverified
7Ours: cross-sentence ALBRE Micro F169.4—Unverified
8MGERE+ Micro F168.2—Unverified
9HySPA (ours) w/ RoBERTaRelation F168.2—Unverified
10RNN+CNNRelation classification F167.7—Unverified
#ModelMetricClaimedVerifiedStatus
1ReLiK-LargeRE+ Micro F178.1—Unverified
2REBELRE+ Macro F1 76.65—Unverified
3ASP+T0-3BRE+ Micro F176.3—Unverified
4Table-SequenceRE+ Macro F1 75.4—Unverified
5SpERTRE+ Macro F1 72.87—Unverified
6DeeperRE+ Macro F1 72.63—Unverified
7TablERTRE+ Micro F172.6—Unverified
8TANLRE+ Micro F172.6—Unverified
9TriMFRE+ Micro F172.35—Unverified
10Multi-turn QARE+ Micro F168.9—Unverified
#ModelMetricClaimedVerifiedStatus
1PFN (ALBERT XXL, average aggregation)RE+ Macro F183.9—Unverified
2DeeperRE+ Macro F183.74—Unverified
3PFN (ALBERT XXL, no aggregation)RE+ Macro F183.2—Unverified
4SpERT.PL (without overlap and BioBERT)RE+ Macro F182.39—Unverified
5REBEL (including overlapping entities)RE+ Macro F182.2—Unverified
6SpERT.PL (with overlap and BioBERT)RE+ Macro F182.03—Unverified
7CMANRE+ Macro F181.14—Unverified
8Table-SequenceRE+ Macro F180.1—Unverified
9CLDR + CLNERRE+ Macro F179.97—Unverified
10SpERT (without overlap)RE+ Macro F179.24—Unverified
#ModelMetricClaimedVerifiedStatus
1UniRelF194.7—Unverified
2PFNF193.6—Unverified
3SPNF193.4—Unverified
4TDEERF193.1—Unverified
5RIFREF192.6—Unverified
6TPLinkerF191.9—Unverified
7HBT (CasRel)F191.8—Unverified
8RIN (BERT, K=2)F190.1—Unverified
9CGT(UniLM)F183.4—Unverified