ALNER: ARABIC LOCATION NAMED ENTITIES
The British University in Dubai (BUiD)
This dissertation describes a rule based approach carried out to determine Location Named Entities in Arabic. ALNER, an Arabic Location Named Entities Recognition system, implements the rule based approach and is introduced in this thesis. This research is the first of its type to specialize in Location NER as a stand-alone system from other named entity types. Such dedication on one named entities helps in investigating the performance of comprehensive NER systems. The Named Entity Recognition (NER) task has great influence on various Natural Language Processing (NLP) applications (e.g. Information Retrieval, Question Answering, etc.). Various research works conducted toward building language independent NER systems that will work on any language but very limited work has been done for NER systems to work with Arabic language. It is known that Arabic language has complex morphology as a language which makes the NER task more difficult. Readers will find an overview about the Arabic language morphology and how it is different from other languages. We also highlighted the key challenges in Arabic language for the NER task. In addition, overall presentation about previous work toward Arabic NER is presented. ALNER system using rule-based approach was evaluated and achieved accuracy of 87.27% and further investigation was conducted to study per module effectiveness and contribution.
entities recognition, ALNER