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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1851–1900 of 1977 papers

TitleStatusHype
Towards a More Generalized Approach in Open Relation ExtractionCode0
Paths to Relation Extraction through Semantic StructureCode0
SUNNYNLP at SemEval-2018 Task 10: A Support-Vector-Machine-Based Method for Detecting Semantic Difference using Taxonomy and Word Embedding FeaturesCode0
End-to-End Relation Extraction using LSTMs on Sequences and Tree StructuresCode0
Towards a relation extraction framework for cyber-security conceptsCode0
SagDRE: Sequence-Aware Graph-Based Document-Level Relation Extraction with Adaptive Margin LossCode0
Cross-lingual Inference with A Chinese Entailment GraphCode0
End-to-end neural relation extraction using deep biaffine attentionCode0
LASIGE and UNICAGE solution to the NASA LitCoin NLP CompetitionCode0
End-to-End n-ary Relation Extraction for Combination Drug TherapiesCode0
LayoutLMv2: Multi-modal Pre-training for Visually-Rich Document UnderstandingCode0
LayoutLMv3: Pre-training for Document AI with Unified Text and Image MaskingCode0
Biomedical Event Extraction as Multi-turn Question AnsweringCode0
VaeDiff-DocRE: End-to-end Data Augmentation Framework for Document-level Relation ExtractionCode0
Towards a Search Engine for Machines: Unified Ranking for Multiple Retrieval-Augmented Large Language ModelsCode0
Learn from Relation Information: Towards Prototype Representation Rectification for Few-Shot Relation ExtractionCode0
Supporting Medical Relation Extraction via Causality-Pruned Semantic Dependency ForestCode0
Two Training Strategies for Improving Relation Extraction over Universal GraphCode0
Deep Structured Neural Network for Event Temporal Relation ExtractionCode0
Learning Discriminative Representations for Open Relation Extraction with Instance Ranking and Label CalibrationCode0
Learning Dual Retrieval Module for Semi-supervised Relation ExtractionCode0
Beyond Word Attention: Using Segment Attention in Neural Relation ExtractionCode0
CRIM at SemEval-2018 Task 9: A Hybrid Approach to Hypernym DiscoveryCode0
End-to-end Named Entity Recognition and Relation Extraction using Pre-trained Language ModelsCode0
EmRel: Joint Representation of Entities and Embedded Relations for Multi-triple ExtractionCode0
Towards Better Document-level Relation Extraction via Iterative InferenceCode0
Position-aware Attention and Supervised Data Improve Slot FillingCode0
Position-aware Self-attention with Relative Positional Encodings for Slot FillingCode0
BERT-Based Multi-Head Selection for Joint Entity-Relation ExtractionCode0
Empowering Few-Shot Relation Extraction with The Integration of Traditional RE Methods and Large Language ModelsCode0
BEKG: A Built Environment Knowledge GraphCode0
Empower Distantly Supervised Relation Extraction with Collaborative Adversarial TrainingCode0
Synergistic Anchored Contrastive Pre-training for Few-Shot Relation ExtractionCode0
Learning Relatedness between Types with Prototypes for Relation ExtractionCode0
SeeDev Binary Event Extraction using SVMs and a Rich Feature SetCode0
Preserving Generalization of Language models in Few-shot Continual Relation ExtractionCode0
Learning Relation Entailment with Structured and Textual InformationCode0
Embedding Lexical Features via Low-Rank TensorsCode0
Pretrained Knowledge Base Embeddings for improved Sentential Relation ExtractionCode0
Towards Better Graph-based Cross-document Relation Extraction via Non-bridge Entity Enhancement and Prediction DebiasingCode0
Eliciting Knowledge from Experts:Automatic Transcript Parsing for Cognitive Task AnalysisCode0
Eliciting Knowledge from Experts: Automatic Transcript Parsing for Cognitive Task AnalysisCode0
A Causal View of Entity Bias in (Large) Language ModelsCode0
Learning from Explanations with Neural Execution TreeCode0
Learning to Compose Domain-Specific Transformations for Data AugmentationCode0
Learning to Few-Shot Learn Across Diverse Natural Language Classification TasksCode0
Crake: Causal-Enhanced Table-Filler for Question Answering over Large Scale Knowledge BaseCode0
XFormParser: A Simple and Effective Multimodal Multilingual Semi-structured Form ParserCode0
Efficient Joint Learning for Clinical Named Entity Recognition and Relation Extraction Using Fourier Networks: A Use Case in Adverse Drug EventsCode0
X-WikiRE: A Large, Multilingual Resource for Relation Extraction as Machine ComprehensionCode0
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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
8KnowPromptF190.3—Unverified
9LUKEF190.3—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
7TANLRE+ Micro F172.6—Unverified
8TablERTRE+ 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