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 751–800 of 1977 papers

TitleStatusHype
RCL: Relation Contrastive Learning for Zero-Shot Relation ExtractionCode0
HITSZ-HLT at SemEval-2022 Task 10: A Span-Relation Extraction Framework for Structured Sentiment Analysis—0
JBNU-CCLab at SemEval-2022 Task 12: Machine Reading Comprehension and Span Pair Classification for Linking Mathematical Symbols to Their DescriptionsCode0
Improving Distantly Supervised Document-Level Relation Extraction Through Natural Language Inference—0
Exploring Text Representations for Generative Temporal Relation Extraction—0
Event Causality Identification via Generation of Important Context WordsCode0
AIFB-WebScience at SemEval-2022 Task 12: Relation Extraction First - Using Relation Extraction to Identify EntitiesCode0
Ensemble-based Fine-Tuning Strategy for Temporal Relation Extraction from the Clinical Narrative—0
A Human-machine Interface for Few-shot Rule Synthesis for Information Extraction—0
EmRel: Joint Representation of Entities and Embedded Relations for Multi-triple ExtractionCode0
Prompt Augmented Generative Replay via Supervised Contrastive Learning for Lifelong Intent Detection—0
Learn from Relation Information: Towards Prototype Representation Rectification for Few-Shot Relation ExtractionCode0
Joint Extraction of Entities, Relations, and Events via Modeling Inter-Instance and Inter-Label Dependencies—0
Permutation Invariant Strategy Using Transformer Encoders for Table Understanding—0
Learning Discriminative Representations for Open Relation Extraction with Instance Ranking and Label CalibrationCode0
Dependency Position Encoding for Relation Extraction—0
Generic and Trend-aware Curriculum Learning for Relation Extraction—0
Enhancing Targeted Minority Class Prediction in Sentence-Level Relation ExtractionCode0
Contextualization and Generalization in Entity and Relation Extraction—0
REKnow: Enhanced Knowledge for Joint Entity and Relation Extraction—0
STable: Table Generation Framework for Encoder-Decoder Models—0
Always Keep your Target in Mind: Studying Semantics and Improving Performance of Neural Lexical SubstitutionCode0
DeepREF: A Framework for Optimized Deep Learning-based Relation ClassificationCode0
JaMIE: A Pipeline Japanese Medical Information Extraction System with Novel Relation AnnotationCode0
The CRECIL Corpus: a New Dataset for Extraction of Relations between Characters in Chinese Multi-party DialoguesCode0
How’s Business Going Worldwide ? A Multilingual Annotated Corpus for Business Relation Extraction—0
Enhancing Relation Extraction via Adversarial Multi-task LearningCode0
Enhanced Distant Supervision with State-Change Information for Relation ExtractionCode0
A Graph-Based Method for Unsupervised Knowledge Discovery from Financial Texts—0
Holistic Evaluation of Automatic TimeML Annotators—0
Large Language Models are Few-Shot Clinical Information Extractors—0
Fine-grained Contrastive Learning for Relation ExtractionCode0
TAGPRIME: A Unified Framework for Relational Structure ExtractionCode0
Improving Long Tailed Document-Level Relation Extraction via Easy Relation Augmentation and Contrastive Learning—0
Relation Extraction with Weighted Contrastive Pre-training on Distant SupervisionCode0
Generic and Trend-aware Curriculum Learning for Relation Extraction in Graph Neural Networks—0
Pre-trained Language Models as Re-Annotators—0
LayoutXLM vs. GNN: An Empirical Evaluation of Relation Extraction for Documents—0
GRAPHCACHE: Message Passing as Caching for Sentence-Level Relation Extraction—0
Unified Semantic Typing with Meaningful Label InferenceCode0
Relation Extraction as Open-book Examination: Retrieval-enhanced Prompt TuningCode0
Modeling Task Interactions in Document-Level Joint Entity and Relation Extraction—0
Textual Entailment for Event Argument Extraction: Zero- and Few-Shot with Multi-Source Learning—0
Biographical: A Semi-Supervised Relation Extraction Dataset—0
Improving Supervised Drug-Protein Relation Extraction with Distantly Supervised Models—0
Comparing Encoder-Only and Encoder-Decoder Transformers for Relation Extraction from Biomedical Texts: An Empirical Study on Ten Benchmark Datasets—0
Improving Discriminative Learning for Zero-Shot Relation Extraction—0
Improving Relation Extraction through Syntax-induced Pre-training with Dependency MaskingCode0
Pretrained Knowledge Base Embeddings for improved Sentential Relation ExtractionCode0
Extraction of Diagnostic Reasoning Relations for Clinical Knowledge Graphs—0
Show:102550
← PrevPage 16 of 40Next →
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