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Arabert Ner
A
Arabert Ner
Developed by abdusah
This is a model for Arabic named entity recognition, capable of identifying entities such as person names, place names, and organization names in text.
Sequence Labeling
Transformers Supports Multiple Languages#Arabic NER#Multilingual Entity Recognition#Text Information Extraction
Transformers Downloads 97
Release Time : 3/2/2022
Model Overview
This model focuses on the task of named entity recognition in Arabic text and can be used to extract structured information from Arabic text.
Model Features
Arabic Language Support
Named entity recognition capabilities specifically optimized for Arabic text.
Multi-category Recognition
Capable of identifying various entity types such as person names, place names, and organization names.
Pre-trained Model
Pre-trained on the WikiANN dataset, providing out-of-the-box recognition capabilities.
Model Capabilities
Arabic Text Processing
Named Entity Recognition
Information Extraction
Use Cases
Information Extraction
News Analysis
Extracting information about people, places, and organizations from Arabic news.
Automatically identifies key entities mentioned in the news.
Academic Research
Processing entity information in Arabic academic literature.
Helps researchers quickly locate key entities in the literature.
Business Intelligence
Customer Data Analysis
Analyzing entity information in Arabic customer data.
Automatically identifies companies, products, and other information mentioned by customers.
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