1. The Named Entity Recognition (NER)
• Al-Shehri ,Aisha
• Almutairi ,Shaikhah
• Alswelim ,Haya
KINGDOM OF SAUDI ARABIA
Ministry of Higher Education
Al-Imam Muhammad Ibn Saud Islamic
University
College of Computer and Information Sciences
2. Abstract
Name Entity Recognition is an important part of many natural
language processing tasks .
There are different type of name entity such as people ,
location and organization .
3. Introduction
• The Named Entity Recognition is the identification and
classification of Named Entities within an open-domain text.
• The task of named entity recognition was defined as three
subtasks:
• ENAMEX.
• TIMEX, and NUMEX.
4. • We present the attempt at the recognition and
extraction of the most important proper name entity, that is,
the person name, for the Arabic language(PERA).
Components of an Arabic Full Name:
divided into five main categories, Ibn Auda (2003):
1. An ism (pronounced IZM).
2. A kunya (pronounced COON-yah).
3. By a nasab (pronounced NAH-sahb).
4. A laqab (pronounced LAH-kahb).
5. A nisba (pronounced NISS-bah).
6. Challenges
• 1- There is no capital letters or a specific signal in the
orthography like many other language.
• 2-The Arabic has different meaning
• 3-Abiguity
12. SystemArchitectureand Implementation
2) Grammar:
The grammar performs recognition and extraction of Arabic
named entities from the input text based on derived rules.
The following are examples of indicators used within rules:
• Job title: (the doctor), (the sciences
professor).
• Person title: (Mr.) , (Mrs.).
13. SystemArchitectureand Implementation
3) Filter:
filter rules hels in dealing with recognition
ambiguity between named entities.
filtration mechanism is used that serves two different
purposes:revision of the NE extractor results and
disambiguation
of matches returned by different NE extractors.
17. Conclusion
• 1-We tried in the majority of cases to follow more general
criteria, applicable on English-Arabic transliteration or
French-Arabic transliteration.
• 2-This work is part of a new system for Arabic NER. It has
several ongoing activities.
18. References
• Sherief Abdallah, Khaled Shaalan, and Muhammad Shoaib ,
Integrating Rule-Based System with Classification for Arabic
Named Entity Recognition, 2012
• Yassine Benajiba , Mona Diab , and Paolo Rosso ,Using
Language Independent and Language Specific Features to
Enhance Arabic Named Entity Recognition, 2009
• Yassine Benajiba , Mona Diab , and Paolo Rosso , Arabic
Named Entity Recognition: AN SVM-BASED APPROACH, 2009
• Doaa Samy, Antonio Moreno, and José Mª Guirao, A Proposal
For An Arabic Named Entity Tagger Leveraging aParallel
Corpus,2005
• Khaled Shaalan, Hafsa Raza, Person Name Entity Recognition
for Arabic,2009