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 1401–1450 of 1977 papers

TitleStatusHype
Incremental Joint Extraction of Entity Mentions and Relations—0
Inferring Missing Entity Type Instances for Knowledge Base Completion: New Dataset and Methods—0
Inferring User Preferences by Probabilistic Logical Reasoning over Social Networks—0
Information Extraction: An application to the domain of hyper-local financial data on developing countries—0
Information Extraction from Biomedical Texts: Learning Models with Limited Supervision—0
Information Extraction from German Patient Records via Hybrid Parsing and Relation Extraction Strategies—0
TINKER: A framework for Open source Cyberthreat Intelligence—0
Infusing clinical knowledge into tokenisers for language models—0
Infusion of Labeled Data into Distant Supervision for Relation Extraction—0
InSRL: A Multi-view Learning Framework Fusing Multiple Information Sources for Distantly-supervised Relation Extraction—0
Integrating Deep Learning with Logic Fusion for Information Extraction—0
Integrating Heterogeneous Domain Information into Relation Extraction: A Case Study on Drug-Drug Interaction Extraction—0
Integrating Word Embedding Offsets into the Espresso System for Part-Whole Relation Extraction—0
Integration of Deep Learning and Traditional Machine Learning for Knowledge Extraction from Biomedical Literature—0
Interactive Relation Extraction in Main Memory Database Systems—0
Interfacing Sentential and Discourse TAG-based Grammars—0
Interim Report on Human-Guided Adaptive Hyperparameter Optimization with Multi-Fidelity Sprints—0
Interpretability Rules: Jointly Bootstrapping a Neural Relation Extractorwith an Explanation Decoder—0
Inter-sentence Relation Extraction for Associating Biological Context with Events in Biomedical Texts—0
Inter-sentence Relation Extraction with Document-level Graph Convolutional Neural Network—0
Introducing DRAIL -- a Step Towards Declarative Deep Relational Learning—0
Investigating LSTMs for Joint Extraction of Opinion Entities and Relations—0
Investigating the Challenges of Temporal Relation Extraction from Clinical Text—0
Investigation of BERT Model on Biomedical Relation Extraction Based on Revised Fine-tuning Mechanism—0
Investigations on Knowledge Base Embedding for Relation Prediction and Extraction—0
Invited Talk: The Case for Universal Dependencies—0
IRCMS at SemEval-2018 Task 7 : Evaluating a basic CNN Method and Traditional Pipeline Method for Relation Classification—0
Is artificial data useful for biomedical Natural Language Processing algorithms?—0
"Is depression related to cannabis?": A knowledge-infused model for Entity and Relation Extraction with Limited Supervision—0
Is ``hot pizza'' Positive or Negative? Mining Target-aware Sentiment Lexicons—0
ITNLP-ARC at SemEval-2018 Task 12: Argument Reasoning Comprehension with Attention—0
Jargon-Term Extraction by Chunking—0
基于平行交互注意力网络的中文电子病历实体及关系联合抽取(Parallel Interactive Attention Network for Joint Entity and Relation Extraction Based on Chinese Electronic Medical Record)—0
基于深度学习的实体关系抽取研究综述(Review of Entity Relation Extraction based on deep learning)—0
Joint Constrained Learning for Event-Event Relation Extraction—0
Joint Entity and Relation Extraction for Legal Documents with Legal Feature Enhancement—0
Joint Event and Temporal Relation Extraction with Shared Representations and Structured Prediction—0
Joint extraction of entities and overlapping relations using position-attentive sequence labeling—0
Jointly Modeling Hierarchical and Horizontal Features for Relational Triple Extraction—0
Joint Extraction of Entities, Relations, and Events via Modeling Inter-Instance and Inter-Label Dependencies—0
Joint Extraction of Entity and Relation with Information Redundancy Elimination—0
Joint Extraction of Uyghur Medicine Knowledge with Edge Computing—0
Joint Inference for Knowledge Base Population—0
Joint Learning-based Causal Relation Extraction from Biomedical Literature—0
Joint Learning with Pre-trained Transformer on Named Entity Recognition and Relation Extraction Tasks for Clinical Analytics—0
Jointly Embedding Relations and Mentions for Knowledge Population—0
Jointly Extracting Multiple Triplets with Multilayer Translation Constraints—0
Jointly Learning Clinical Entities and Relations with Contextual Language Models and Explicit Context—0
Joint Mention Extraction and Classification with Mention Hypergraphs—0
Jointprop: Joint Semi-supervised Learning for Entity and Relation Extraction with Heterogeneous Graph-based Propagation—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