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 401–450 of 1977 papers

TitleStatusHype
GCRE-GPT: A Generative Model for Comparative Relation Extraction—0
Clinical Concept and Relation Extraction Using Prompt-based Machine Reading Comprehension—0
Dynamic Multi-View Fusion Mechanism For Chinese Relation Extraction—0
Comprehensive Event Representations using Event Knowledge Graphs and Natural Language Processing—0
Does Synthetic Data Generation of LLMs Help Clinical Text Mining?—0
Document-level Relation Extraction with Cross-sentence Reasoning GraphCode0
NLP Workbench: Efficient and Extensible Integration of State-of-the-art Text Mining ToolsCode0
90% F1 Score in Relational Triple Extraction: Is it Real ?—0
DREEAM: Guiding Attention with Evidence for Improving Document-Level Relation ExtractionCode1
Event Temporal Relation Extraction with Bayesian Translational Model—0
Lightweight Transformers for Clinical Natural Language ProcessingCode1
Efficient Joint Learning for Clinical Named Entity Recognition and Relation Extraction Using Fourier Networks: A Use Case in Adverse Drug EventsCode0
FGSI: Distant Supervision for Relation Extraction method based on Fine-Grained Semantic Information—0
Bioformer: an efficient transformer language model for biomedical text miningCode1
Large Language Models for Biomedical Knowledge Graph Construction: Information extraction from EMR notes—0
NLP as a Lens for Causal Analysis and Perception Mining to Infer Mental Health on Social Media—0
Task formulation for Extracting Social Determinants of Health from Clinical Narratives—0
Weakly-Supervised Questions for Zero-Shot Relation ExtractionCode0
Learning Trajectory-Conditioned Relations to Predict Pedestrian Crossing BehaviorCode0
Contrast with Major Classifier Vectors for Federated Medical Relation Extraction with Heterogeneous Label Distribution—0
Multilingual Entity and Relation Extraction from Unified to Language-specific Training—0
ReVoLT: Relational Reasoning and Voronoi Local Graph Planning for Target-driven Navigation—0
Reviewing Labels: Label Graph Network with Top-k Prediction Set for Relation Extraction—0
Sequence Generation with Label Augmentation for Relation ExtractionCode1
Integrating Heterogeneous Domain Information into Relation Extraction: A Case Study on Drug-Drug Interaction Extraction—0
Continual Contrastive Finetuning Improves Low-Resource Relation Extraction—0
ImPaKT: A Dataset for Open-Schema Knowledge Base Construction—0
Can NLI Provide Proper Indirect Supervision for Low-resource Biomedical Relation Extraction?Code1
Multi-hop Evidence Retrieval for Cross-document Relation ExtractionCode1
Document-level Relation Extraction with Relation CorrelationsCode0
Enriching Relation Extraction with OpenIE—0
Leveraging Natural Language Processing to Augment Structured Social Determinants of Health Data in the Electronic Health RecordCode0
Structured information extraction from complex scientific text with fine-tuned large language models—0
Cross-Domain Few-Shot Relation Extraction via Representation Learning and Domain Adaptation—0
Named Entity and Relation Extraction with Multi-Modal Retrieval—0
CliMedBERT: A Pre-trained Language Model for Climate and Health-related Text—0
Focus! Relevant and Sufficient Context Selection for News Image Captioning—0
Open Relation and Event Type Discovery with Type AbstractionCode1
Joint Multimodal Entity-Relation Extraction Based on Edge-enhanced Graph Alignment Network and Word-pair Relation TaggingCode1
Towards Better Document-level Relation Extraction via Iterative InferenceCode0
Learning with Silver Standard Data for Zero-shot Relation Extraction—0
A Dataset for Hyper-Relational Extraction and a Cube-Filling ApproachCode1
UniRel: Unified Representation and Interaction for Joint Relational Triple ExtractionCode1
MAVEN-ERE: A Unified Large-scale Dataset for Event Coreference, Temporal, Causal, and Subevent Relation ExtractionCode1
On Analyzing the Role of Image for Visual-enhanced Relation ExtractionCode0
CCPrefix: Counterfactual Contrastive Prefix-Tuning for Many-Class Classification—0
Unimodal and Multimodal Representation Training for Relation Extraction—0
Gradient Imitation Reinforcement Learning for General Low-Resource Information Extraction—0
Towards automating Numerical Consistency Checks in Financial Reports—0
Not Just Plain Text! Fuel Document-Level Relation Extraction with Explicit Syntax Refinement and Subsentence Modeling—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