Title: Psychological named entity recognition from psychological Arabic texts

Authors: Kheira Lakel; Fatima Bendella

Addresses: Department of Computer Science, Faculty of Science, USTO University, BP 1505, 31000, Algeria ' Department of Computer Science, Faculty of Science, USTO University, BP 1505, 31000, Algeria

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.

DOI: 10.1504/IJMSO.2017.090758

International Journal of Metadata, Semantics and Ontologies, 2017 Vol.12 No.2/3, pp.82 - 89

Received: 13 Dec 2016
Accepted: 12 Sep 2017
Published online: 27 Mar 2018 *

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