Relation Extraction
Relation extraction is the task of predicting the attributes of entities and their mutual relationships in a sentence, aiming to identify and classify the relationships between entities in the text. This task is crucial for building relational knowledge graphs and can significantly enhance the performance of natural language processing applications such as structured search, sentiment analysis, question answering systems, and text summarization.
DocRED
DREEAM
TACRED
DeepStruct multi-task w/ finetune
SemEval-2010 Task-8
ACE 2005
Multi-turn QA
CoNLL04
REBEL
Adverse Drug Events (ADE) Corpus
ITER
WebNLG
PFN
ChemProt
SciBert (Finetune)
NYT11-HRL
RERE
ACE 2004
PL-Marker
CDR
SAISORE+CR+ET-SciBERT
NYT10-HRL
ReRe
FUNSD
GDA
Re-TACRED
SpanBERT
NYT
NYT Corpus
KGPOOL
ReDocRED
DREEAM
SemEval 2018 Task 10
SVM with GloVe
NYT21
DDI
KeBioLM
DWIE
GAD
BioLinkBERT (large)
NYT-single
ETL-Span
NYT29
SciERC
PFN
SKE
ReRe (exact)
TACRED-Revisited
BioRED
PubMedBERT
Dataset: Relationship extraction for knowledge graph creation from biomedical literature (Gene-Disease relationships)
FewRel
ERNIE
NYT24
WDec
REBEL
SemEval-2010 Task 8
LLM-QA4RE (XXLarge)
WLPC
SpanRel
2010 i2b2/VA
Spark NLP
2012 i2b2 Temporal Relations
Spark NLP
2018 n2c2 posology
Spark NLP
ADE Corpus
PFN
Dataset: Relationship extraction for knowledge graph creation from biomedical literature (Gene-Disease relationships) n
DuIE
Google RE
JNLPBA
SciBERT (SciVocab)
LPSC-contains
LPSC-hasproperty
Stacked_LinkedBERT
MUC6
iDepNN
PGR
Spark NLP
sciERC-sent
RELA
Wikipedia-Wikidata relations
ContextAtt
WNUT 2020
Baseline