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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1651–1700 of 1977 papers

TitleStatusHype
DUTIR in BioNLP-ST 2016: Utilizing Convolutional Network and Distributed Representation to Extract Complicate Relations—0
Relation Classification via Multi-Level Attention CNNs—0
Character based String Kernels for Bio-Entity Relation Detection—0
Identification of Mentions and Relations between Bacteria and Biotope from PubMed Abstracts—0
LitWay, Discriminative Extraction for Different Bio-Events—0
Neural Relation Extraction with Selective Attention over InstancesCode0
Improving Temporal Relation Extraction with Training Instance Augmentation—0
Extraction of Regulatory Events using Kernel-based Classifiers and Distant Supervision—0
Natural Solution to FraCaS Entailment Problems—0
Multi-source named entity typing for social media—0
Attention-Based Bidirectional Long Short-Term Memory Networks for Relation ClassificationCode0
Learning Relational Dependency Networks for Relation Extraction—0
Relation extraction from clinical texts using domain invariant convolutional neural network—0
Leveraging Semantic Web Search and Browse Sessions for Multi-Turn Spoken Dialog Systems—0
Focused Meeting Summarization via Unsupervised Relation Extraction—0
Bootstrapping Distantly Supervised IE using Joint Learning and Small Well-structured Corpora—0
CDE-IIITH at SemEval-2016 Task 12: Extraction of Temporal Information from Clinical documents using Machine Learning techniques—0
JUNLP at SemEval-2016 Task 13: A Language Independent Approach for Hypernym Identification—0
Using Graphs of Classifiers to Impose Constraints on Semi-supervised Relation Extraction—0
Interfacing Sentential and Discourse TAG-based Grammars—0
Incorporating Selectional Preferences in Multi-hop Relation Extraction—0
LIMSI-COT at SemEval-2016 Task 12: Temporal relation identification using a pipeline of classifiers—0
Call for Discussion: Building a New Standard Dataset for Relation Extraction Tasks—0
Mapping Verbs in Different Languages to Knowledge Base Relations using Web Text as Interlingua—0
Data-driven Paraphrasing and Stylistic Harmonization—0
A Comparison of Weak Supervision methods for Knowledge Base Construction—0
Effective Crowd Annotation for Relation Extraction—0
Automatic Extraction of Causal Relations from Natural Language Texts: A Comprehensive Survey—0
Grammatical Case Based IS-A Relation Extraction with Boosting for Polish—0
Relation- and Phrase-level Linking of FrameNet with Sar-graphs—0
Sentence Similarity based on Dependency Tree Kernels for Multi-document Summarization—0
A Sequence Model Approach to Relation Extraction in Portuguese—0
More than Word Cooccurrence: Exploring Support and Opposition in International Climate Negotiations with Semantic Parsing—0
TEG-REP: A corpus of Textual Entailment Graphs based on Relation Extraction Patterns—0
Semantic Relation Extraction with Semantic Patterns Experiment on Radiology Reports—0
Extracting Temporal and Causal Relations between Events—0
Embedding Lexical Features via Low-Rank TensorsCode0
Question Answering on Freebase via Relation Extraction and Textual EvidenceCode0
Numerical Atrribute Extraction from Clinical Texts—0
End-to-End Relation Extraction using LSTMs on Sequences and Tree StructuresCode0
Generating Training Data for Semantic Role Labeling based on Label Transfer from Linked Lexical Resources—0
Discrete-State Variational Autoencoders for Joint Discovery and Factorization of RelationsCode0
Using Entity Information from a Knowledge Base to Improve Relation Extraction—0
Bootstrapping Ternary Relation Extractors—0
Multilingual Relation Extraction using Compositional Universal SchemaCode0
Combining Neural Networks and Log-linear Models to Improve Relation Extraction—0
Fast and Large-scale Unsupervised Relation Extraction—0
Bidirectional Long Short-Term Memory Networks for Relation Classification—0
Improving distant supervision using inference learning—0
Large-Scale Acquisition of Entailment Pattern Pairs by Exploiting Transitivity—0
Show:102550
← PrevPage 34 of 40Next →
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