82 Int. J. Metadata, Semantics and Ontologies, Vol. 12, Nos. 2/3, 2017 Copyright © 2017 Inderscience Enterprises Ltd. Psychological named entity recognition from psychological Arabic texts Kheira Lakel* and Fatima Bendella Department of Computer Science, Faculty of Science, USTO University, BP 1505, 31000, Algeria Email: kheira.lakel@univ-usto.dz Email: fatima.bendella@univ-usto.dz *Corresponding author Abstract: The most important problems facing the Arabisation of modern science is the terminological inconsistency in translation; this problem becomes more complex in the medical field specifically in psychological sciences where the translation of English–Arabic medical terms poses real challenges for researchers eager to analyse and organise this information. Arabic NER (Named Entity Recognition) systems play a significant role in many areas of Natural Language Processing (NLP). In this paper, the problem of PsyNER (Psychological Named Entity Recognition) is tackled through integrating the rule-based and machine learning based approach to form a hybrid approach in attempt to enhance the overall performance of PsyNER. This system is capable to recognise eight types of named entities including mental disorders designated by the DSM-IV (Diagnostic and Statistical Manual of the American Psychiatric Association). Keywords: NERA; named entity recognition; psychological sciences; Arabic language; Jape; gazetteers; GATE. Reference to this paper should be made as follows: Lakel, K. and Bendella, F. (2017) ‘Psychological named entity recognition from psychological Arabic texts’, Int. J. Metadata, Semantics and Ontologies, Vol. 12, Nos. 2/3, pp.82–89. Biographical notes: Kheira Lakel is a PhD student at USTO University. Her PhD topic is about Ontologies, Semantic Web and Natural Language Processing. She has published research papers at national and international conference proceedings. Fatima Bendella is a Professor at the Computer Science Department of USTO University (Algeria). Her research interests are related to MAS (Multi-Agent System), Natural Language Processing and Serious Game. She has published research papers at national and international journals, conference proceedings as well as chapters of books. 1 Introduction During the Islamic era in 7th century, Arabic medicine and pharmacology reached their peak, more specifically during the Umayyad and Abbasside periods, when movements of translation into Arabic flourished, followed by a period of Arabic contributions. The history of Arabic medicine extended from the 8th century when Arab intellectualists started to appear and multiple sciences began to emerge eastward. This beacon of sciences remained there until the beginning of the 13th century. The history of Arabic medicine can be divided into three main stages; the age of translation, the age of Arabic original contribution, and the age of decline and transmission to Europe (Najjar, 2010). Arabic is one of the six official languages of the United Nations. It is spoken by 300 million people in the 23 countries of the Arab world. It is one of the Semitic languages. The treatment of the Arab language is considered complex because structural and morphological characteristics such as inflection, polysemy and irregular word forms; and for various reasons, today Arab medicine suffers from the terminological inconsistency and several attempts to put the official Arabic language in several medical institutes have proved futile. Another evidence of the lack of Arabic in the Semantic Web world is a recent statistic provided by the (OntoSelect) ontology library (Buitelaar and Eigner, 2008), which shows that 71% of the ontologies with labels in the library are created in English. This problem could be attributed to the lack of tools and software development environments that process Arabic script in all steps of the semantic annotation process.