Abstract
Named Entity Recognition (NER) is a computational linguistic concept that is used to find and classify appropriate nouns in a text such as person names, geographical locations, and organizations. Such a concept is fundamental in the field of natural language processing. In Libya, many private and public institutions suffer from using the proper translation of entity names from Arabic language into English. Therefore, in this paper, we are concerned with analyzing Arabic articles to extract and recognize entity names. A recognition system is developed for recognizing names of persons, academic institutions, and cities in Libya. At first, a training corpus and dictionaries are built for the intended entity names in this research. Then, the aspects of the entity names are studied, and their patterns and rules are designed. Then, the implementation is performed using Nooj linguistic language. The recognition of person names and Libyan cities and academic institutions was carried out. Statistics showed the frequencies of the appearance rate of person names, academic institutions, and cities in our training corpus. The obtained results are promised and met the research goals for tackling the problem of Arabic named entity recognition.
Highlights
Natural language processing (NLP) is an area that can be used to realize and process natural language text to accomplish valuable tasks by computers
Recognition of Libyan Academic Institutions Recognition of Libyan academic institutions are obtained by applying the designed grammars and org’ Nooj dictionary on the created corpus
SYSTEM EVALUATION For the evaluation and performance of our designed system, we have statistically showed the appearance rate of person name, academic institutions, and cities frequencies in our training corpus
Summary
Natural language processing (NLP) is an area that can be used to realize and process natural language text to accomplish valuable tasks by computers. The aim of NLP comprises building of real computational applications to explore the features of natural language used by human and to develop systems including the smart processing of human written language via computer. NER can be defined as the task that attempts to find and classify named entities into predefined classes or types in open-domain and unstructured texts, such as newspaper articles. It is a part of data classification applications in specific fields such as sport, agriculture, medicine, etc. The main goal is providing the Libyan society recently and in the future with important services through proposing an informatics system to recognize the concerned entity names and translating them properly from Arabic to English.
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