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SOTA
中文命名实体识别
Chinese Named Entity Recognition On Ontonotes
Chinese Named Entity Recognition On Ontonotes
评估指标
F1
Precision
Recall
评测结果
各个模型在此基准测试上的表现结果
Columns
模型名称
F1
Precision
Recall
Paper Title
Repository
BERT-MRC+DSC
84.47
-
-
Dice Loss for Data-imbalanced NLP Tasks
W2NER
83.08
-
-
Unified Named Entity Recognition as Word-Word Relation Classification
Baseline + BS
82.83
-
-
Boundary Smoothing for Named Entity Recognition
BERT-MRC
82.11
-
-
A Unified MRC Framework for Named Entity Recognition
FGN
82.04
-
-
FGN: Fusion Glyph Network for Chinese Named Entity Recognition
FLAT+BERT
81.82
-
-
FLAT: Chinese NER Using Flat-Lattice Transformer
AESINER
81.18
-
-
Improving Named Entity Recognition with Attentive Ensemble of Syntactic Information
Glyce + BERT
80.62
81.87
81.4
Glyce: Glyph-vectors for Chinese Character Representations
SLK-NER
80.2
-
-
SLK-NER: Exploiting Second-order Lexicon Knowledge for Chinese NER
NFLAT
77.21
75.17
79.37
NFLAT: Non-Flat-Lattice Transformer for Chinese Named Entity Recognition
FLAT
76.45
-
-
FLAT: Chinese NER Using Flat-Lattice Transformer
LSTM + Lexicon augment
75.54
-
-
Simplify the Usage of Lexicon in Chinese NER
LGN
74.89
76.13
73.68
A Lexicon-Based Graph Neural Network for Chinese NER
-
Lattice
73.88
-
-
Chinese NER Using Lattice LSTM
CAN-NER Model
73.64
75.05
72.29
CAN-NER: Convolutional Attention Network for Chinese Named Entity Recognition
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