Relation Extraction
关系抽取是预测句子中实体属性及其相互关系的任务，旨在识别和分类文本中的实体间关系。该任务对于构建关系知识图谱至关重要，能够显著提升结构化搜索、情感分析、问答系统和文本摘要等自然语言处理应用的效果。
2010 i2b2/VA
Spark NLP
2012 i2b2 Temporal Relations
Spark NLP
2018 n2c2 posology
Spark NLP
ACE 2004
PL-Marker
ACE 2005
PL-Marker
Adverse Drug Events (ADE) Corpus
ITER
ADE Corpus
PFN
BioRED
PubMedBERT
CDR
SAISORE+CR+ET-SciBERT
ChemProt
PubMedBERT uncased
CoNLL04
ASP+T0-3B
Dataset: Relationship extraction for knowledge graph creation from biomedical literature (Gene-Disease relationships)
Dataset: Relationship extraction for knowledge graph creation from biomedical literature (Gene-Disease relationships) n
DDI
BioLinkBERT (large)
DocRED
DREEAM
DuIE
DWIE
FewRel
RoCORE
FUNSD
GAD
BioLinkBERT (large)
GDA
Google RE
JNLPBA
SciBERT (SciVocab)
LPSC-contains
LPSC-hasproperty
Stacked_LinkedBERT
MUC6
iDepNN
NYT
NYT Corpus
KGPOOL
NYT-single
ETL-Span
NYT10-HRL
ReRe
NYT11-HRL
RERE
NYT21
NYT24
WDec
NYT29
PGR
Spark NLP
Re-TACRED
SpanBERT
REBEL
ReDocRED
DREEAM
SciERC
PFN
sciERC-sent
RELA
SemEval-2010 Task-8
SemEval-2010 Task 8
LLM-QA4RE (XXLarge)
SemEval 2018 Task 10
SVM with GloVe
SKE
ReRe (exact)
TACRED
RAG4RE
TACRED-Revisited
WebNLG
UniRel
Wikipedia-Wikidata relations
ContextAtt
WLPC
SpanRel
WNUT 2020
Baseline