ArabicNER-Wojood Open-source Model - Free for Named Entity Recognition in Modern and Dialectal Arabic

Arabicner Wojood

Developed by SinaLab

Wojood is a corpus for Arabic nested named entity recognition (NER), containing 550,000 word instances (Modern Standard Arabic and dialects).

Downloads 19

Release Time : 3/20/2023

Model Overview

This model is used for Arabic nested named entity recognition (NER), capable of identifying entity mentions nested within another entity.

Nested Entity Recognition

Capable of identifying entities nested within other entities, which is typically challenging for traditional NER models.

Arabic Language Support

An NER model specifically optimized for Arabic (including dialects).

High Performance

Achieves a micro-averaged F1 score of 0.909551 on nested NER tasks and 0.883847 on flat NER tasks.

Arabic Named Entity Recognition

Nested Entity Recognition

Flat Entity Recognition

Natural Language Processing

Arabic Text Analysis

Extract named entities from Arabic texts for applications such as information extraction and knowledge graph construction.

Accurately identifies nested entities in texts.

Arabic Dialect Processing

Handle named entity recognition tasks in Modern Standard Arabic and dialects.

Demonstrates strong recognition capabilities for Arabic dialects.

Property	Details
Model Type	Nested/Flat Arabic NER Models
Training Data	Wojood Corpus
Metrics	F1, Precision, Recall
Pipeline Tag	Token - Classification
Tags	Named Entity Recognition, Arabic NER, Nested NER
Language	Arabic

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