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 1001–1050 of 1977 papers

TitleStatusHype
Implementing a Portable Clinical NLP System with a Common Data Model - a Lisp Perspective—0
Importance weighting and unsupervised domain adaptation of POS taggers: a negative result—0
Bacteria Biotope Detection, Ontology-based Normalization, and Relation Extraction using Syntactic Rules—0
Improved Decomposition Strategy for Joint Entity and Relation Extraction—0
VulCPE: Context-Aware Cybersecurity Vulnerability Retrieval and Management—0
A Zero-shot and Few-shot Study of Instruction-Finetuned Large Language Models Applied to Clinical and Biomedical Tasks—0
A Weighting Scheme for Open Information Extraction—0
Improving Continual Relation Extraction through Prototypical Contrastive Learning—0
A Web-based Tool for the Integrated Annotation of Semantic and Syntactic Structures—0
Improving Cross-Domain Performance for Relation Extraction via Dependency Prediction and Information Flow Control—0
Improving Discriminative Learning for Zero-Shot Relation Extraction—0
Improving Distantly Supervised Document-Level Relation Extraction Through Natural Language Inference—0
Improving Distantly Supervised Extraction of Drug-Drug and Protein-Protein Interactions—0
Improving Distantly Supervised Relation Extraction with Neural Noise Converter and Conditional Optimal Selector—0
A Web-based Collaborative Evaluation Tool for Automatically Learned Relation Extraction Patterns—0
Improving Distantly-Supervised Relation Extraction with Joint Label Embedding—0
AutoRD: An Automatic and End-to-End System for Rare Disease Knowledge Graph Construction Based on Ontologies-enhanced Large Language Models—0
TacoERE: Cluster-aware Compression for Event Relation Extraction—0
Improving Distantly-Supervised Relation Extraction through BERT-based Label & Instance Embeddings—0
Improving Distantly Supervised Relation Extraction by Natural Language Inference—0
Improving distant supervision using inference learning—0
A Cueing Strategy for Prompt Tuning in Relation Extraction—0
TagNText: A parallel corpus for the induction of resource-specific non-taxonomical relations from tagged images—0
Improving Document-level Relation Extraction via Context Guided Mention Integration and Inter-pair Reasoning—0
Automatic Wayang Ontology Construction using Relation Extraction from Free Text—0
Improving Knowledge Base Construction from Robust Infobox Extraction—0
Improving Long Tailed Document-Level Relation Extraction via Easy Relation Augmentation and Contrastive Learning—0
Active Testing: An Unbiased Evaluation Method for Distantly Supervised Relation Extraction—0
Automatic semantic relation extraction from Portuguese texts—0
TakeLab at SemEval-2018 Task 7: Combining Sparse and Dense Features for Relation Classification in Scientific Texts—0
Automatic Food Categorization from Large Unlabeled Corpora and Its Impact on Relation Extraction—0
Improving Neural Relation Extraction with Positive and Unlabeled Learning—0
Improving NLP through Marginalization of Hidden Syntactic Structure—0
Improving Open Relation Extraction via Sentence Re-Structuring—0
Improving Performance of Relation Extraction Algorithm via Leveled Adversarial PCNN and Database Expansion—0
Improving Persian Relation Extraction Models by Data Augmentation—0
Task formulation for Extracting Social Determinants of Health from Clinical Narratives—0
Improving Relation Classification by Entity Pair Graph—0
Zero-shot Relation Classification as Textual Entailment—0
Active Relation Discovery: Towards General and Label-aware Open Relation Extraction—0
TDRE: A Tensor Decomposition Based Approach for Relation Extraction—0
Improving Relation Extraction with Knowledge-attention—0
Techniques for Jointly Extracting Entities and Relations: A Survey—0
Improving Scholarly Knowledge Representation: Evaluating BERT-based Models for Scientific Relation Classification—0
Improving Semantic Parsing via Answer Type Inference—0
Improving Sentence-Level Relation Extraction through Curriculum Learning—0
Improving Slot Filling Performance with Attentive Neural Networks on Dependency Structures—0
Improving Supervised Drug-Protein Relation Extraction with Distantly Supervised Models—0
Improving Temporal Relation Extraction with Training Instance Augmentation—0
Improving Temporal Relation Extraction with a Globally Acquired Statistical Resource—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
8LUKEF190.3—Unverified
9KnowPromptF190.3—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
7TablERTRE+ Micro F172.6—Unverified
8TANLRE+ 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