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 1901–1950 of 1977 papers

TitleStatusHype
Employing Word Representations and Regularization for Domain Adaptation of Relation Extraction—0
Semi-Automating Knowledge Base Construction for Cancer Genetics—0
Unsupervised Relation Extraction of In-Domain Data from Focused Crawls—0
EmRel: Joint Representation of Entities and Embedded Relations for Multi-triple Extraction—0
Semi-Supervised Learning with Declaratively Specified Entropy Constraints—0
Encoding Implicit Relation Requirements for Relation Extraction: A Joint Inference Approach—0
Encoding Relation Requirements for Relation Extraction via Joint Inference—0
End-to-End Argument Mining as Biaffine Dependency Parsing—0
End-to-End Hierarchical Relation Extraction for Generic Form Understanding—0
End-to-End Models for Chemical-Protein Interaction Extraction: Better Tokenization and Span-Based Pipeline Strategies—0
A Framework for Compiling High Quality Knowledge Resources From Raw Corpora—0
Semi-supervised Relation Extraction via Data Augmentation and Consistency-training—0
Semi-Supervised Teacher-Student Architecture for Relation Extraction—0
End-to-End Neural Relation Extraction with Global Optimization—0
Unsupervised Relation Extraction with General Domain Knowledge—0
End-to-End Relation Extraction using Markov Logic Networks—0
End-to-end Relation Extraction using Neural Networks and Markov Logic Networks—0
UNTER: A Unified Knowledge Interface for Enhancing Pre-trained Language Models—0
Sentence-Level Relation Extraction via Contrastive Learning with Descriptive Relation Prompts—0
End-to-End Trainable Retrieval-Augmented Generation for Relation Extraction—0
Sentence Similarity based on Dependency Tree Kernels for Multi-document Summarization—0
Building a Japanese Corpus of Temporal-Causal-Discourse Structures Based on SDRT for Extracting Causal Relations—0
Enhanced Protein-Protein Interactions Extraction from the Literature using Entity Type- and Position-aware Representation—0
UPB at SemEval-2021 Task 8: Extracting Semantic Information on Measurements as Multi-Turn Question Answering—0
Building a Corpus for Biomedical Relation Extraction of Species Mentions—0
Senti-LSSVM: Sentiment-Oriented Multi-Relation Extraction with Latent Structural SVM—0
Bridge Text and Knowledge by Learning Multi-Prototype Entity Mention Embedding—0
Enhancing Contrastive Learning with Noise-Guided Attack: Towards Continual Relation Extraction in the Wild—0
Enhancing Dialogue-based Relation Extraction by Speaker and Trigger Words Prediction—0
Enhancing Document Information Analysis with Multi-Task Pre-training: A Robust Approach for Information Extraction in Visually-Rich Documents—0
Brand-Product Relation Extraction Using Heterogeneous Vector Space Representations—0
AMR-RE: Abstract Meaning Representations for Retrieval-Based In-Context Learning in Relation Extraction—0
Enhancing Knowledge Graph Construction Using Large Language Models—0
A Feature-Enriched Tree Kernel for Relation Extraction—0
Enhancing Multimodal Entity and Relation Extraction with Variational Information Bottleneck—0
Separating Retention from Extraction in the Evaluation of End-to-end Relation Extraction—0
Seq2rel: A sequence-to-sequence-based approach for document-level relation extraction—0
Adversarial Training for Relation Extraction—0
Adversarial Learning for Supervised and Semi-supervised Relation Extraction in Biomedical Literature—0
Enhancing Software-Related Information Extraction via Single-Choice Question Answering with Large Language Models—0
Enhancing Supply Chain Visibility with Knowledge Graphs and Large Language Models—0
SetExpander: End-to-end Term Set Expansion Based on Multi-Context Term Embeddings—0
Should We Rely on Entity Mentions for Relation Extraction? Debiasing Relation Extraction with Counterfactual Analysis—0
Enriched Attention for Robust Relation Extraction—0
Advancing Relation Extraction through Language Probing with Exemplars from Set Co-Expansion—0
Enriching Relation Extraction with OpenIE—0
BOUN-ISIK Participation: An Unsupervised Approach for the Named Entity Normalization and Relation Extraction of Bacteria Biotopes—0
Ensemble-based Fine-Tuning Strategy for Temporal Relation Extraction from the Clinical Narrative—0
Ensemble-Based Medical Relation Classification—0
Ensemble Making Few-Shot Learning Stronger—0
Show:102550
← PrevPage 39 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