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 901–950 of 1977 papers

TitleStatusHype
Benchmarking Biomedical Nested NER and Relation Extraction Models—0
On the Relation between Syntactic Divergence and Zero-Shot PerformanceCode0
Process Extraction from Text: Benchmarking the State of the Art and Paving the Way for Future ChallengesCode0
FoodChem: A food-chemical relation extraction modelCode0
Enhancing Biomedical Relation Extraction with Transformer Models using Shortest Dependency Path Features and Triplet InformationCode0
Generate Triggers in Neural Relation Extraction—0
Multi-scale fusion self attention mechanism—0
Logic Pre-Training of Language Models—0
Entity Linking Meets Deep Learning: Techniques and Solutions—0
Separating Retention from Extraction in the Evaluation of End-to-end Relation Extraction—0
Extracting Fine-Grained Knowledge Graphs of Scientific Claims: Dataset and Transformer-Based Results—0
Hierarchical Relation-Guided Type-Sentence Alignment for Long-Tail Relation Extraction with Distant Supervision—0
Meta-Learning with Sparse Experience Replay for Lifelong Language Learning—0
RelO: An Overlapping Relation Extraction Dataset and ModelCode0
Slot Filling for Biomedical Information ExtractionCode0
DiS-ReX: A Multilingual Dataset for Distantly Supervised Relation Extraction—0
Modular Self-Supervision for Document-Level Relation Extraction—0
Speaker-Oriented Latent Structures for Dialogue-Based Relation ExtractionCode0
D-REX: Dialogue Relation Extraction with ExplanationsCode0
How May I Help You? Using Neural Text Simplification to Improve Downstream NLP TasksCode0
MapRE: An Effective Semantic Mapping Approach for Low-resource Relation Extraction—0
Label Verbalization and Entailment for Effective Zero- and Few-Shot Relation Extraction—0
Knowing False Negatives: An Adversarial Training Method for Distantly Supervised Relation ExtractionCode0
Multilingual Epidemic Event Extraction : From Simple Classification Methods to Open Information Extraction (OIE) and Ontology—0
Extracting all Aspect-polarity Pairs Jointly in a Text with Relation Extraction Approach—0
Relation Extraction Using Multiple Pre-Training Models in Biomedical Domain—0
Active Learning for Interactive Relation Extraction in a French Newspaper’s Articles—0
Predicting Informativeness of Semantic Triples—0
TREND: Trigger-Enhanced Relation-Extraction Network for DialoguesCode0
Towards Learning Terminological Concept Systems from Multilingual Natural Language TextCode0
Relation Extraction from Tables using Artificially Generated Metadata—0
Improving Distantly Supervised Relation Extraction with Self-Ensemble Noise FilteringCode0
A Hierarchical Entity Graph Convolutional Network for Relation Extraction across DocumentsCode0
Extracting Radiological Findings With Normalized Anatomical Information Using a Span-Based BERT Relation Extraction Model—0
RTE: A Tool for Annotating Relation Triplets from Text—0
Extracting Semantics from Maintenance Records—0
GrantRel: Grant Information Extraction via Joint Entity and Relation Extraction—0
A Unified Representation Learning Strategy for Open Relation Extraction with Ranked List Loss—0
Refining Sample Embeddings with Relation Prototypes to Enhance Continual Relation ExtractionCode0
From What to Why: Improving Relation Extraction with Rationale Graph—0
A Trigger-Aware Multi-Task Learning for Chinese Event Entity Recognition—0
CONNER: A Cascade Count and Measurement Extraction Tool for Scientific Discourse—0
TIMERS: Document-level Temporal Relation Extraction—0
面向对话文本的实体关系抽取(Entity Relation Extraction for Dialogue Text)—0
KGP at SemEval-2021 Task 8: Leveraging Multi-Staged Language Models for Extracting Measurements, their Attributes and RelationsCode0
Meta Learning and Its Applications to Natural Language Processing—0
Paths to Relation Extraction through Semantic StructureCode0
Entity and Evidence Guided Document-Level Relation Extraction—0
Enhancing Dialogue-based Relation Extraction by Speaker and Trigger Words Prediction—0
DPR at SemEval-2021 Task 8: Dynamic Path Reasoning for Measurement 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