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

Showing 12011250 of 1977 papers

TitleStatusHype
KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language RepresentationCode0
Leveraging Dependency Forest for Neural Medical Relation ExtractionCode0
Learning to Few-Shot Learn Across Diverse Natural Language Classification TasksCode0
Generalizing Natural Language Analysis through Span-relation RepresentationsCode0
Towards Understanding Gender Bias in Relation ExtractionCode0
Neural Graph Embedding Methods for Natural Language ProcessingCode0
Relation Adversarial Network for Low Resource Knowledge Graph Completion0
Learning from Explanations with Neural Execution TreeCode0
On the Effectiveness of the Pooling Methods for Biomedical Relation Extraction with Deep Learning0
Learning the Extraction Order of Multiple Relational Facts in a Sentence with Reinforcement Learning0
Trigger Word Detection and Thematic Role Identification via BERT and Multitask Learning0
BOUN-ISIK Participation: An Unsupervised Approach for the Named Entity Normalization and Relation Extraction of Bacteria Biotopes0
Self-Attention Enhanced CNNs and Collaborative Curriculum Learning for Distantly Supervised Relation Extraction0
A Constituency Parsing Tree based Method for Relation Extraction from Abstracts of Scholarly Publications0
Open Relation Extraction: Relational Knowledge Transfer from Supervised Data to Unsupervised DataCode0
KnowledgeNet: A Benchmark Dataset for Knowledge Base PopulationCode0
Improving Distantly-Supervised Relation Extraction with Joint Label Embedding0
Cross-lingual Structure Transfer for Relation and Event Extraction0
Bacteria Biotope Relation Extraction via Lexical Chains and Dependency Graphs0
Cross-Sentence N-ary Relation Extraction using Lower-Arity Universal Schemas0
Easy First Relation Extraction with Information Redundancy0
Relation Extraction among Multiple Entities Using a Dual Pointer Network with a Multi-Head Attention Mechanism0
Extracting Complex Relations from Banking Documents0
Towards Extracting Medical Family History from Natural Language Interactions: A New Dataset and Baselines0
Deep Bidirectional Transformers for Relation Extraction without Supervision0
Recognizing UMLS Semantic Types with Deep Learning0
DeepGeneMD: A Joint Deep Learning Model for Extracting Gene Mutation-Disease Knowledge from PubMed Literature0
An Overview of the Active Gene Annotation Corpus and the BioNLP OST 2019 AGAC Track TasksCode0
YNU-junyi in BioNLP-OST 2019: Using CNN-LSTM Model with Embeddings for SeeDev Binary Event Extraction0
Distant Supervised Relation Extraction with Separate Head-Tail CNN0
Syntax-aware Multi-task Graph Convolutional Networks for Biomedical Relation Extraction0
Nearly-Unsupervised Hashcode Representations for Biomedical Relation Extraction0
Integration of Deep Learning and Traditional Machine Learning for Knowledge Extraction from Biomedical Literature0
A Multi-Task Learning Framework for Extracting Bacteria Biotope Information0
Neural Cross-Lingual Relation Extraction Based on Bilingual Word Embedding Mapping0
Attention-Gated Graph Convolutions for Extracting Drug Interaction Information from Drug Labels0
A Survey on Recent Advances in Named Entity Recognition from Deep Learning modelsCode0
HiExpan: Task-Guided Taxonomy Construction by Hierarchical Tree Expansion0
Learning High-order Structural and Attribute information by Knowledge Graph Attention Networks for Enhancing Knowledge Graph Embedding0
Linguistically Informed Relation Extraction and Neural Architectures for Nested Named Entity Recognition in BioNLP-OST 2019Code0
Improving Relation Extraction with Knowledge-attention0
Extracting UMLS Concepts from Medical Text Using General and Domain-Specific Deep Learning Models0
MTab: Matching Tabular Data to Knowledge Graph using Probability ModelsCode0
Biomedical relation extraction with pre-trained language representations and minimal task-specific architecture0
Fine-tune Bert for DocRED with Two-step ProcessCode0
Deep Structured Neural Network for Event Temporal Relation ExtractionCode0
Span-based Joint Entity and Relation Extraction with Transformer Pre-trainingCode0
Neural Correction Model for Open-Domain Named Entity RecognitionCode0
Taxonomical hierarchy of canonicalized relations from multiple Knowledge BasesCode0
Leveraging 2-hop Distant Supervision from Table Entity Pairs for Relation ExtractionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DREEAMF167.53Unverified
2KD-Rb-lF167.28Unverified
3SSAN-RoBERTa-large+AdaptationF165.92Unverified
4SAIS-RoBERTa-largeF165.11Unverified
5Eider-RoBERTa-largeF164.79Unverified
6DocuNet-RoBERTa-largeF164.55Unverified
7CGM2IR-RoBERTalargeF163.89Unverified
8SETE-Roberta-largeF163.74Unverified
9ATLOP-RoBERTa-largeF163.4Unverified
10DRE-MIR-BERTbaseF163.15Unverified
#ModelMetricClaimedVerifiedStatus
1RAG4REF186.6Unverified
2DeepStruct multi-task w/ finetuneF176.8Unverified
3UNiST (LARGE)F175.5Unverified
4RE-MCF175.4Unverified
5GenPT (T5)F175.3Unverified
6RECENT+SpanBERTF175.2Unverified
7SuRE (PEGASUS-large)F175.1Unverified
8EXOBRAINF175Unverified
9Relation ReductionF174.8Unverified
10RoBERTa-large-typed-markerF174.6Unverified
#ModelMetricClaimedVerifiedStatus
1SPF191.9Unverified
2RIFREF191.3Unverified
3REDNF191Unverified
4SPOTF190.6Unverified
5KLGF190.5Unverified
6RELAF190.4Unverified
7Skeleton-Aware BERTF190.36Unverified
8KnowPromptF190.3Unverified
9LUKEF190.3Unverified
10EPGNNF190.2Unverified
#ModelMetricClaimedVerifiedStatus
1Span-levelNER Micro F185.98Unverified
2Dual Pointer Network(multi-head)Relation classification F180.8Unverified
3Dual Pointer NetworkRelation classification F180.5Unverified
4PL-MarkerRE Micro F173Unverified
5ASP+T5-3BRE Micro F172.7Unverified
6GoLLIERE Micro F170.1Unverified
7Ours: cross-sentence ALBRE Micro F169.4Unverified
8MGERE+ Micro F168.2Unverified
9HySPA (ours) w/ RoBERTaRelation F168.2Unverified
10RNN+CNNRelation classification F167.7Unverified
#ModelMetricClaimedVerifiedStatus
1ReLiK-LargeRE+ Micro F178.1Unverified
2REBELRE+ Macro F1 76.65Unverified
3ASP+T0-3BRE+ Micro F176.3Unverified
4Table-SequenceRE+ Macro F1 75.4Unverified
5SpERTRE+ Macro F1 72.87Unverified
6DeeperRE+ Macro F1 72.63Unverified
7TANLRE+ Micro F172.6Unverified
8TablERTRE+ Micro F172.6Unverified
9TriMFRE+ Micro F172.35Unverified
10Multi-turn QARE+ Micro F168.9Unverified
#ModelMetricClaimedVerifiedStatus
1PFN (ALBERT XXL, average aggregation)RE+ Macro F183.9Unverified
2DeeperRE+ Macro F183.74Unverified
3PFN (ALBERT XXL, no aggregation)RE+ Macro F183.2Unverified
4SpERT.PL (without overlap and BioBERT)RE+ Macro F182.39Unverified
5REBEL (including overlapping entities)RE+ Macro F182.2Unverified
6SpERT.PL (with overlap and BioBERT)RE+ Macro F182.03Unverified
7CMANRE+ Macro F181.14Unverified
8Table-SequenceRE+ Macro F180.1Unverified
9CLDR + CLNERRE+ Macro F179.97Unverified
10SpERT (without overlap)RE+ Macro F179.24Unverified
#ModelMetricClaimedVerifiedStatus
1UniRelF194.7Unverified
2PFNF193.6Unverified
3SPNF193.4Unverified
4TDEERF193.1Unverified
5RIFREF192.6Unverified
6TPLinkerF191.9Unverified
7HBT (CasRel)F191.8Unverified
8RIN (BERT, K=2)F190.1Unverified
9CGT(UniLM)F183.4Unverified