Named Entity Recognition On Anatem
Métriques
F1
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | F1 | Paper Title | Repository |
|---|---|---|---|
| aimped | 91.08 | - | - |
| BertForTokenClassification (Spark NLP) | 91.65 | Accurate clinical and biomedical Named entity recognition at scale | |
| BLSTM-CNN-Char (SparkNLP) | 89.13 | Biomedical Named Entity Recognition at Scale | - |
| ConNER | 83.5 | Enhancing Label Consistency on Document-level Named Entity Recognition | |
| UniNER-7B | 88.65 | UniversalNER: Targeted Distillation from Large Language Models for Open Named Entity Recognition |
0 of 5 row(s) selected.