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 1851–1900 of 1977 papers

TitleStatusHype
Semantic relation clustering for unsupervised information extraction (Regroupement s\'emantique de relations pour l'extraction d'information non supervis\'ee) [in French]—0
Causality Extraction from Nuclear Licensee Event Reports Using a Hybrid Framework—0
Cascaded Models for Better Fine-Grained Named Entity Recognition—0
DP-CRE: Continual Relation Extraction via Decoupled Contrastive Learning and Memory Structure Preservation—0
DPR at SemEval-2021 Task 8: Dynamic Path Reasoning for Measurement Relation Extraction—0
Semantic Relation Extraction from a Cultural Database—0
CARE: Extracting Experimental Findings From Clinical Literature—0
Semantic Relation Extraction with Semantic Patterns Experiment on Radiology Reports—0
DRK: Discriminative Rule-based Knowledge for Relieving Prediction Confusions in Few-shot Relation Extraction—0
DSGAN: Generative Adversarial Training for Distant Supervision Relation Extraction—0
Dual Architecture for Name Entity Extraction and Relation Extraction with Applications in Medical Corpora—0
Dual-Gated Fusion with Prefix-Tuning for Multi-Modal Relation Extraction—0
Dual Pointer Network for Fast Extraction of Multiple Relations in a Sentence—0
Semantic Representations for Domain Adaptation: A Case Study on the Tree Kernel-based Method for Relation Extraction—0
DUTIR in BioNLP-ST 2016: Utilizing Convolutional Network and Distributed Representation to Extract Complicate Relations—0
CANDiS: Coupled & Attention-Driven Neural Distant Supervision—0
Dynamic Graph Transformer for Implicit Tag Recognition—0
Dynamic Knowledge-Base Alignment for Coreference Resolution—0
Dynamic Multi-View Fusion Mechanism For Chinese Relation Extraction—0
Dynamic Relation Transformer for Contextual Text Block Detection—0
Easy First Relation Extraction with Information Redundancy—0
SemEval-2010 Task 13: TempEval-2—0
SemEval-2013 Task 1: TempEval-3: Evaluating Time Expressions, Events, and Temporal Relations—0
Can AI Extract Antecedent Factors of Human Trust in AI? An Application of Information Extraction for Scientific Literature in Behavioural and Computer Sciences—0
Effective Crowd Annotation for Relation Extraction—0
Effective Crowdsourcing of Multiple Tasks for Comprehensive Knowledge Extraction—0
Call for Discussion: Building a New Standard Dataset for Relation Extraction Tasks—0
Building Contextual Knowledge Graphs for Personalized Learning Recommendations using Text Mining and Semantic Graph Completion—0
Effectiveness and Efficiency of Open Relation Extraction—0
Effective Selectional Restrictions for Unsupervised Relation Extraction—0
Effective Slot Filling Based on Shallow Distant Supervision Methods—0
Effect of Non-linear Deep Architecture in Sequence Labeling—0
Effects of Human Adversarial and Affable Samples on BERT Generalization—0
SemEval-2014 Task 6: Supervised Semantic Parsing of Robotic Spatial Commands—0
SemEval-2015 Task 4: TimeLine: Cross-Document Event Ordering—0
Efficient long-distance relation extraction with DG-SpanBERT—0
Building Chinese Event Type Paradigm Based on Trigger Clustering—0
Building a Multimodal Entity Linking Dataset From Tweets—0
EIDER: Evidence-enhanced Document-level Relation Extraction—0
Building a Japanese Document-Level Relation Extraction Dataset Assisted by Cross-Lingual Transfer—0
Element Intervention for Open Relation Extraction—0
SemEval-2018 Task 7: Semantic Relation Extraction and Classification in Scientific Papers—0
SemEval-2020 Task 6: Definition extraction from free text with the DEFT corpus—0
ELiRF-UPV at SemEval-2018 Task 10: Capturing Discriminative Attributes with Knowledge Graphs and Wikipedia—0
A Framework for Developing and Evaluating Word Embeddings of Drug-named Entity—0
Embedding Methods for Fine Grained Entity Type Classification—0
Embedding Semantic Similarity in Tree Kernels for Domain Adaptation of Relation Extraction—0
EMBRE: Entity-aware Masking for Biomedical Relation Extraction—0
Emphasis on Easy Samples for Distantly Supervised Relation Extraction—0
Empirical Analysis of Dialogue Relation Extraction with Large Language Models—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
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