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 851–900 of 1977 papers

TitleStatusHype
Contextual Argument Component Classification for Class Discussions—0
DSGAN: Generative Adversarial Training for Distant Supervision Relation Extraction—0
Attention-Based Capsule Networks with Dynamic Routing for Relation Extraction—0
Interactive Relation Extraction in Main Memory Database Systems—0
BomJi at SemEval-2018 Task 10: Combining Vector-, Pattern- and Graph-based Information to Identify Discriminative Attributes—0
Focused Entailment Graphs for Open IE Propositions—0
Focused Meeting Summarization via Unsupervised Relation Extraction—0
Focus! Relevant and Sufficient Context Selection for News Image Captioning—0
Continual Contrastive Finetuning Improves Low-Resource Relation Extraction—0
Attention-Gated Graph Convolutions for Extracting Drug Interaction Information from Drug Labels—0
HAREM and Klue: how to put two tagsets for named entities annotation together—0
Freepal: A Large Collection of Deep Lexico-Syntactic Patterns for Relation Extraction—0
DRK: Discriminative Rule-based Knowledge for Relieving Prediction Confusions in Few-shot Relation Extraction—0
Contrastive Triple Extraction with Generative Transformer—0
BitCoin: Bidirectional Tagging and Supervised Contrastive Learning based Joint Relational Triple Extraction Framework—0
From What to Why: Improving Relation Extraction with Rationale Graph—0
Controlled Randomness Improves the Performance of Transformer Models—0
A Comprehensive Survey of Document-level Relation Extraction (2016-2023)—0
GADePo: Graph-Assisted Declarative Pooling Transformers for Document-Level Relation Extraction—0
GAN Driven Semi-distant Supervision for Relation Extraction—0
GatorTron: A Large Clinical Language Model to Unlock Patient Information from Unstructured Electronic Health Records—0
GCRE-GPT: A Generative Model for Comparative Relation Extraction—0
GDA: Generative Data Augmentation Techniques for Relation Extraction Tasks—0
Active Testing: An Unbiased Evaluation Method for Distantly Supervised Relation Extraction—0
BIOS: An Algorithmically Generated Biomedical Knowledge Graph—0
Generalising and Normalising Distributional Contexts to Reduce Data Sparsity: Application to Medical Corpora—0
Principles from Clinical Research for NLP Model Generalization—0
Generalized knowledge-enhanced framework for biomedical entity and relation extraction—0
Antonym-Synonym Classification Based on New Sub-space Embeddings—0
Generalizing through Forgetting -- Domain Generalization for Symptom Event Extraction in Clinical Notes—0
Generate it. A simple method for End-to-End Relation Extraction—0
Generate Triggers in Neural Relation Extraction—0
Generating Diverse Training Samples for Relation Extraction with Large Language Models—0
Generating Pattern-Based Entailment Graphs for Relation Extraction—0
GUIR at SemEval-2017 Task 12: A Framework for Cross-Domain Clinical Temporal Information Extraction—0
Generative Large Language Models Are All-purpose Text Analytics Engines: Text-to-text Learning Is All Your Need—0
DPR at SemEval-2021 Task 8: Dynamic Path Reasoning for Measurement Relation Extraction—0
DP-CRE: Continual Relation Extraction via Decoupled Contrastive Learning and Memory Structure Preservation—0
Generic and Trend-aware Curriculum Learning for Relation Extraction in Graph Neural Networks—0
Generic and Trend-aware Curriculum Learning for Relation Extraction—0
Answer Extraction by Recursive Parse Tree Descent—0
Harvesting Parallel News Streams to Generate Paraphrases of Event Relations—0
Genre Separation Network with Adversarial Training for Cross-genre Relation Extraction—0
Counterfactual Thinking for Long-tailed Information Extraction—0
Held-out versus Gold Standard: Comparison of Evaluation Strategies for Distantly Supervised Relation Extraction from Medline abstracts—0
Do the Benefits of Joint Models for Relation Extraction Extend to Document-level Tasks?—0
A German Corpus for Fine-Grained Named Entity Recognition and Relation Extraction of Traffic and Industry Events—0
GIELLM: Japanese General Information Extraction Large Language Model Utilizing Mutual Reinforcement Effect—0
GLiNER multi-task: Generalist Lightweight Model for Various Information Extraction Tasks—0
GREG: A Global Level Relation Extraction with Knowledge Graph Embedding—0
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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