ARABIC PERSON NAMES RECOGNITION BY USING A RULE BASED APPROACH

Abstract

Name Entity Recognition is very important task in many natural language processing applications such as; Machine Translation, Question Answering, Information Extraction, Text Summarization, Semantic Applications and Word Sense Disambiguation. Rule-based approach is one of the techniques that are used for named entity recognition to identify the named entities such as a person names, location names and organization names. The recent rule-based methods have been applied to recognize the person names in political domain. They ignored the recognition of other named entity types such as locations and organizations. We have used the rule based approach for recognizing the named entity type (person names) for Arabic. We have developed four rules for identifying the person names depending on the position of name. We have used an in-house Arabic corpus collected from newspaper achieves. The evaluation method that compares the results of the system with the manually annotated text has been applied in order to compute precision, recall and f-measure. In the experiment of this study, the average f-measure for recognizing person names are (92.66, 92.04 and 90.43%) in sport, economic and politic domain respectively. The experimental results showed that our rule-based method achieved the highest f-measure values in sport domain comparing with political and economic domains.