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SOTA
中文命名实体识别
Chinese Named Entity Recognition On Resume
Chinese Named Entity Recognition On Resume
评估指标
F1
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
Paper Title
Repository
Baseline + BS
96.66
Boundary Smoothing for Named Entity Recognition
-
Lattice
94.46
Chinese NER Using Lattice LSTM
-
AESINER
96.62
Improving Named Entity Recognition with Attentive Ensemble of Syntactic Information
-
FLAT
95.45
FLAT: Chinese NER Using Flat-Lattice Transformer
-
Glyce + BERT
96.54
Glyce: Glyph-vectors for Chinese Character Representations
-
FLAT+BERT
95.86
FLAT: Chinese NER Using Flat-Lattice Transformer
-
FGN
96.79
FGN: Fusion Glyph Network for Chinese Named Entity Recognition
-
TENER
95
TENER: Adapting Transformer Encoder for Named Entity Recognition
-
LSTM + Lexicon augment
95.59
Simplify the Usage of Lexicon in Chinese NER
-
SLK-NER
95.8
SLK-NER: Exploiting Second-order Lexicon Knowledge for Chinese NER
-
BERT-CRF (Replicated in AdaSeq)
96.87
Improving Named Entity Recognition by External Context Retrieving and Cooperative Learning
-
NFLAT
95.58
NFLAT: Non-Flat-Lattice Transformer for Chinese Named Entity Recognition
-
CAN-NER Model
94.94
CAN-NER: Convolutional Attention Network for Chinese Named Entity Recognition
-
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