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المنصة
الرئيسية
SOTA
التعرف على الكيانات المسماة الصينية
Chinese Named Entity Recognition On Msra
Chinese Named Entity Recognition On Msra
المقاييس
F1
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
Columns
اسم النموذج
F1
Paper Title
BERT-MRC+DSC
96.72
Dice Loss for Data-imbalanced NLP Tasks
BERT-CRF (Replicated in AdaSeq)
96.69
Improving Named Entity Recognition by External Context Retrieving and Cooperative Learning
Baseline + BS
96.26
Boundary Smoothing for Named Entity Recognition
W2NER
96.10
Unified Named Entity Recognition as Word-Word Relation Classification
FLAT+BERT
96.09
FLAT: Chinese NER Using Flat-Lattice Transformer
BERT-MRC
95.75
A Unified MRC Framework for Named Entity Recognition
FGN
95.64
FGN: Fusion Glyph Network for Chinese Named Entity Recognition
Glyce + BERT
95.54
Glyce: Glyph-vectors for Chinese Character Representations
ZEN (Init with Chinese BERT)
95.25
ZEN: Pre-training Chinese Text Encoder Enhanced by N-gram Representations
ERNIE 2.0 Large
95
ERNIE 2.0: A Continual Pre-training Framework for Language Understanding
DiffusionNER
94.91
DiffusionNER: Boundary Diffusion for Named Entity Recognition
NFLAT
94.55
NFLAT: Non-Flat-Lattice Transformer for Chinese Named Entity Recognition
FLAT
94.12
FLAT: Chinese NER Using Flat-Lattice Transformer
ERNIE 2.0 Base
93.8
ERNIE 2.0: A Continual Pre-training Framework for Language Understanding
ERNIE
93.8
ERNIE: Enhanced Representation through Knowledge Integration
LSTM + Lexicon augment
93.5
Simplify the Usage of Lexicon in Chinese NER
PIQN
93.48
Parallel Instance Query Network for Named Entity Recognition
ZEN (Random Init)
93.24
ZEN: Pre-training Chinese Text Encoder Enhanced by N-gram Representations
Lattice
93.18
Chinese NER Using Lattice LSTM
CAN-NER Model
92.97
CAN-NER: Convolutional Attention Network for Chinese Named Entity Recognition
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Chinese Named Entity Recognition On Msra | SOTA | HyperAI