Named Entity Recognition Ner On Ontonotes V5

평가 결과

이 벤치마크에서 각 모델의 성능 결과

비교 표

모델 이름	F1
better-feature-integration-for-named-entity	90.85
190910148	89.88
hierarchically-refined-label-attention	88.16
robust-lexical-features-for-improved-neural	87.95
pack-together-entity-and-relation-extraction	91.9
better-feature-integration-for-named-entity	89.04
a-unified-mrc-framework-for-named-entity	91.11
hierarchical-contextualized-representation	87.98
fast-and-accurate-entity-recognition-with	86.99
190910148	88.52
a-joint-model-for-entity-analysis-coreference	84.04
named-entity-recognition-as-dependency	91.3
semi-supervised-sequence-modeling-with-cross	88.81
towards-improving-neural-named-entity	89.94
remedying-bilstm-cnn-deficiency-in-modeling	88.4
a-unified-generative-framework-for-various	90.38
nuner-entity-recognition-encoder-pre-training	89.1
unified-named-entity-recognition-as-word-word	90.50
improving-named-entity-recognition-with	90.32
grn-gated-relation-network-to-enhance	87.67
hierarchical-contextualized-representation	90.30
hero-gang-neural-model-for-named-entity	90.92
diffusionner-boundary-diffusion-for-named	90.66
fast-and-accurate-entity-recognition-with	86.84
named-entity-recognition-with-bidirectional	86.19
parallel-instance-query-network-for-named	90.96
dice-loss-for-data-imbalanced-nlp-tasks	92.07
boundary-smoothing-for-named-entity-1	91.74