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 1501–1550 of 1977 papers

TitleStatusHype
An Auxiliary Classifier Generative Adversarial Framework for Relation Extraction—0
A Comparative Study of Lexical Substitution Approaches based on Neural Language Models—0
A Case Study on Learning a Unified Encoder of Relations—0
Prompt Augmented Generative Replay via Supervised Contrastive Learning for Lifelong Intent Detection—0
Two Step Joint Model for Drug Drug Interaction Extraction—0
Prompting Large Language Models for Clinical Temporal Relation Extraction—0
ZeroShotCeres: Zero-Shot Relation Extraction from Semi-Structured Webpages—0
An Automated Domain Understanding Technique for Knowledge Graph Generation—0
Anaphora Resolution for Improving Spatial Relation Extraction from Text—0
PromptRE: Weakly-Supervised Document-Level Relation Extraction via Prompting-Based Data Programming—0
Type-Aware Distantly Supervised Relation Extraction with Linked Arguments—0
Propagation Strategies for Building Temporal Ontologies—0
Proposition Knowledge Graphs—0
ProtoEM: A Prototype-Enhanced Matching Framework for Event Relation Extraction—0
An Annotated Corpus of Webtables for Information Extraction Tasks—0
Prototypical Representation Learning for Low-resource Knowledge Extraction: Summary and Perspective—0
Pushing the Limits of ChatGPT on NLP Tasks—0
Typed Tensor Decomposition of Knowledge Bases for Relation Extraction—0
An analysis of full-size Russian complexly NER labelled corpus of Internet user reviews on the drugs based on deep learning and language neural nets—0
An Algebra for Feature Extraction—0
UC3M-NII Team at SemEval-2018 Task 7: Semantic Relation Classification in Scientific Papers via Convolutional Neural Network—0
Query-based Instance Discrimination Network for Relational Triple Extraction—0
QUEST: A Natural Language Interface to Relational Databases—0
UEM-UC3M: An Ontology-based named entity recognition system for biomedical texts.—0
RadGraph2: Modeling Disease Progression in Radiology Reports via Hierarchical Information Extraction—0
A Multi-Task Learning Framework for Extracting Bacteria Biotope Information—0
RAMIE: Retrieval-Augmented Multi-task Information Extraction with Large Language Models on Dietary Supplements—0
UHop: An Unrestricted-Hop Relation Extraction Framework for Knowledge-Based Question Answering—0
A Multi-Task Learning Framework for Extracting Drugs and Their Interactions from Drug Labels—0
A Multi-Gate Encoder for Joint Entity and Relation Extraction—0
Abstains from Prediction: Towards Robust Relation Extraction in Real World—0
RDSGAN: Rank-based Distant Supervision Relation Extraction with Generative Adversarial Framework—0
UMichigan: A Conditional Random Field Model for Resolving the Scope of Negation—0
ZORE: A Syntax-based System for Chinese Open Relation Extraction—0
A Masked Image Reconstruction Network for Document-level Relation Extraction—0
Reading The Web with Learned Syntactic-Semantic Inference Rules—0
AmalREC: A Dataset for Relation Extraction and Classification Leveraging Amalgamation of Large Language Models—0
A logic-based relational learning approach to relation extraction: The OntoILPER system—0
Recall, Retrieve and Reason: Towards Better In-Context Relation Extraction—0
Recall Them All: Retrieval-Augmented Language Models for Long Object List Extraction from Long Documents—0
Recipe Instruction Semantics Corpus (RISeC): Resolving Semantic Structure and Zero Anaphora in Recipes—0
Recognizing Chinese Judicial Named Entity using BiLSTM-CRF—0
Recognizing Complex Entity Mentions: A Review and Future Directions—0
Recognizing UMLS Semantic Types with Deep Learning—0
A Lexicalized Tree Kernel for Open Information Extraction—0
Recovering Patient Journeys: A Corpus of Biomedical Entities and Relations on Twitter (BEAR)—0
Recurrent Interaction Network for Jointly Extracting Entities and Classifying Relations—0
Recurrent Interaction Network for Jointly Extracting Entities andClassifying Relations—0
Recurrent Neural Network with Word Embedding for Complaint Classification—0
Redefining Developer Assistance: Through Large Language Models in Software Ecosystem—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