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 1551–1600 of 1977 papers

TitleStatusHype
A LayoutLMv3-Based Model for Enhanced Relation Extraction in Visually-Rich Documents—0
Reduce, Reuse, Recycle: New uses for old QA resources—0
Reducing Wrong Labels in Distant Supervision for Relation Extraction—0
About Evaluation of F1 Score for RECENT Relation Extraction System—0
Event-Arguments Extraction Corpus and Modeling using BERT for Arabic—0
Understanding Clinical Trial Reports: Extracting Medical Entities and Their Relations—0
REFRACTIVE: An Open Source Tool to Extract Knowledge from Syntactic and Semantic Relations—0
Regularized Attentive Capsule Network for Overlapped Relation Extraction—0
Reinforcement Learning-based N-ary Cross-Sentence Relation Extraction—0
REKnow: Enhanced Knowledge for Joint Entity and Relation Extraction—0
Relabeling Distantly Supervised Training Data for Temporal Knowledge Base Population—0
Relabel the Noise: Joint Extraction of Entities and Relations via Cooperative Multiagents—0
Relating Relations: Meta-Relation Extraction from Online Health Forum Posts—0
Relation Adversarial Network for Low Resource Knowledge Graph Completion—0
Understanding Spatial Language in Radiology: Representation Framework, Annotation, and Spatial Relation Extraction from Chest X-ray Reports using Deep Learning—0
Relational Structures and Models for Coreference Resolution—0
Relational Summarization for Corpus Analysis—0
Relation- and Phrase-level Linking of FrameNet with Sar-graphs—0
Understanding Tables in Context Using Standard NLP Toolkits—0
Relation Classification via Multi-Level Attention CNNs—0
Relation Classification with Cognitive Attention Supervision—0
Relation Classification with Entity Type Restriction—0
Relation Extraction among Multiple Entities Using a Dual Pointer Network with a Multi-Head Attention Mechanism—0
A Biomedical Information Extraction Primer for NLP Researchers—0
Relation Classification as Two-way Span-Prediction—0
UniEX: An Effective and Efficient Framework for Unified Information Extraction via a Span-extractive Perspective—0
Relation extraction between the clinical entities based on the shortest dependency path based LSTM—0
Relation Extraction Datasets in the Digital Humanities Domain and their Evaluation with Word Embeddings—0
Relation Extraction from Biomedical and Clinical Text: Unified Multitask Learning Framework—0
Relation extraction from clinical texts using domain invariant convolutional neural network—0
Relation Extraction from Community Generated Question-Answer Pairs—0
Relation Extraction from News Articles (RENA): A Tool for Epidemic Surveillance—0
Relation Extraction from Tables using Artificially Generated Metadata—0
Relation Extraction from Tables using Artificially Generated Metadata—0
Zero-Shot Document-Level Biomedical Relation Extraction via Scenario-based Prompt Design in Two-Stage with LLM—0
Relation Extraction Model Based on Semantic Enhancement Mechanism—0
A language-independent method for the extraction of RDF verbalization templates—0
Relation extraction pattern ranking using word similarity—0
Relation Extraction: Perspective from Convolutional Neural Networks—0
Relation Extraction using Explicit Context Conditioning—0
Relation Extraction Using Large Language Models: A Case Study on Acupuncture Point Locations—0
Relation Extraction Using Multiple Pre-Training Models in Biomedical Domain—0
Zero-shot Event Causality Identification with Question Answering—0
Relation Extraction with Explanation—0
Relation Extraction with Fine-Tuned Large Language Models in Retrieval Augmented Generation Frameworks—0
UniMa at SemEval-2018 Task 7: Semantic Relation Extraction and Classification from Scientific Publications—0
Relation Extraction with Matrix Factorization and Universal Schemas—0
Relation Extraction with Multi-instance Multi-label Convolutional Neural Networks—0
Relation Extraction with Self-determined Graph Convolutional Network—0
Unimodal and Multimodal Representation Training for Relation Extraction—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