
## Wojood - Nested/Flat Arabic NER Models
Wojood is a corpus for Arabic nested Named Entity Recognition (NER). Nested entities occur when one entity mention is embedded inside another entity mention. 550K tokens (MSA and dialect) This repo contains the source-code to train Wojood nested NER.

Online Demo
You can try our model using the demo link below

https://sina.birzeit.edu/wojood/

https://arxiv.org/abs/2205.09651

https://huggingface.co/aubmindlab/bert-base-arabertv2/tree/main

### Models
* Nested NER (main branch), with micro-F1 score of 0.909551
* Flat NER (flat branch), with micro-F1 score 0.883847

### Google Colab Notebooks
You can test our model using our Google Colab notebooks
* Train flat NER: https://gist.github.com/mohammedkhalilia/72c3261734d7715094089bdf4de74b4a
* Evaluate your model using flat NER model: https://gist.github.com/mohammedkhalilia/c807eb1ccb15416b187c32a362001665  
* Train nested NER: https://gist.github.com/mohammedkhalilia/a4d83d4e43682d1efcdf299d41beb3da
* Evaluate your data using nested NER model: https://gist.github.com/mohammedkhalilia/9134510aa2684464f57de7934c97138b
{"language": ["ar"], "license": "mit", "tags": ["Named Entity Recognition", "Arabic NER"], "datasets": ["Wojood"], "metrics": ["f1", "precision", "recall"], "pipeline_tag": "token-classification"}
transformers pytorch bert fill-mask Named Entity Recognition Arabic NER token-classification ar dataset:Wojood arxiv:2205.09651 license:mit autotrain_compatible endpoints_compatible has_space region:us