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 101–150 of 1977 papers

TitleStatusHype
Do LLMs Really Adapt to Domains? An Ontology Learning PerspectiveCode0
Are LLMs Good Annotators for Discourse-level Event Relation Extraction?Code0
Document-level Clinical Entity and Relation Extraction via Knowledge Base-Guided Generation—0
Empowering Few-Shot Relation Extraction with The Integration of Traditional RE Methods and Large Language ModelsCode0
Consistent Document-Level Relation Extraction via CounterfactualsCode0
EVA-Score: Evaluating Abstractive Long-form Summarization on Informativeness through Extraction and Validation—0
Augmenting Document-level Relation Extraction with Efficient Multi-Supervision—0
A Global-Local Attention Mechanism for Relation Classification—0
Combining Supervised Learning and Reinforcement Learning for Multi-Label Classification Tasks with Partial Labels—0
Towards Better Graph-based Cross-document Relation Extraction via Non-bridge Entity Enhancement and Prediction DebiasingCode0
TemPrompt: Multi-Task Prompt Learning for Temporal Relation Extraction in RAG-based Crowdsourcing Systems—0
Relation Extraction with Fine-Tuned Large Language Models in Retrieval Augmented Generation Frameworks—0
Infusing clinical knowledge into tokenisers for language models—0
Exploring Spatial Representations in the Historical Lake District Texts with LLM-based Relation Extraction—0
How Good are LLMs at Relation Extraction under Low-Resource Scenario? Comprehensive EvaluationCode0
Fusion Makes Perfection: An Efficient Multi-Grained Matching Approach for Zero-Shot Relation ExtractionCode0
Analysing zero-shot temporal relation extraction on clinical notes using temporal consistencyCode0
GLiNER multi-task: Generalist Lightweight Model for Various Information Extraction Tasks—0
AMR-RE: Abstract Meaning Representations for Retrieval-Based In-Context Learning in Relation Extraction—0
On the Robustness of Document-Level Relation Extraction Models to Entity Name VariationsCode0
TTM-RE: Memory-Augmented Document-Level Relation ExtractionCode1
End-to-End Trainable Retrieval-Augmented Generation for Relation Extraction—0
Entangled Relations: Leveraging NLI and Meta-analysis to Enhance Biomedical Relation Extraction—0
Reward-based Input Construction for Cross-document Relation ExtractionCode1
PGA-SciRE: Harnessing LLM on Data Augmentation for Enhancing Scientific Relation Extraction—0
BioBERT-based Deep Learning and Merged ChemProt-DrugProt for Enhanced Biomedical Relation Extraction—0
XFormParser: A Simple and Effective Multimodal Multilingual Semi-structured Form ParserCode0
Adapting PromptORE for Modern History: Information Extraction from Hispanic Monarchy Documents of the XVIth CenturyCode0
Knowledge-Driven Cross-Document Relation ExtractionCode0
Knowledge-enhanced Prompt Tuning for Dialogue-based Relation Extraction with Trigger and Label SemanticCode0
Evaluation of large language model performance on the Biomedical Language Understanding and Reasoning Benchmark—0
CNER: A tool Classifier of Named-Entity Relationships—0
Benchmarking Large Language Models on CFLUE -- A Chinese Financial Language Understanding Evaluation DatasetCode3
A Decoupling and Aggregating Framework for Joint Extraction of Entities and Relations—0
TacoERE: Cluster-aware Compression for Event Relation Extraction—0
Stochastic RAG: End-to-End Retrieval-Augmented Generation through Expected Utility Maximization—0
Recall Them All: Retrieval-Augmented Language Models for Long Object List Extraction from Long Documents—0
Enhancing Language Models for Financial Relation Extraction with Named Entities and Part-of-SpeechCode0
BiomedRAG: A Retrieval Augmented Large Language Model for BiomedicineCode1
Towards a Search Engine for Machines: Unified Ranking for Multiple Retrieval-Augmented Large Language ModelsCode0
Graphical Reasoning: LLM-based Semi-Open Relation ExtractionCode0
CRE-LLM: A Domain-Specific Chinese Relation Extraction Framework with Fine-tuned Large Language ModelCode1
Empirical Analysis of Dialogue Relation Extraction with Large Language Models—0
Meta In-Context Learning Makes Large Language Models Better Zero and Few-Shot Relation Extractors—0
Recall, Retrieve and Reason: Towards Better In-Context Relation Extraction—0
Building a Japanese Document-Level Relation Extraction Dataset Assisted by Cross-Lingual Transfer—0
EnzChemRED, a rich enzyme chemistry relation extraction dataset—0
A Continual Relation Extraction Approach for Knowledge Graph Completeness—0
Fine-Grained Named Entities for Corona NewsCode0
Retrieval-Augmented Generation-based Relation ExtractionCode2
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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