kojose Kocaeli Journal of Science and Engineering 2667-484X Kocaeli University 10.34088/kojose.871873 Computer Software Bilgisayar Yazılımı Named Entity Recognition in Turkish Bank Documents https://orcid.org/0000-0003-1187-5147 Kabasakal Osman KOCAELİ ÜNİVERSİTESİ https://orcid.org/0000-0003-0547-0653 Mutlu Alev KOCAELİ ÜNİVERSİTESİ 11 30 2021 4 2 86 92 01 31 2021 04 13 2021 Copyright © 2018, Kocaeli Journal of Science and Engineering 2018 Kocaeli Journal of Science and Engineering

Named Entity Recognition (NER) is the process of automatically recognizing entity names such as person, organization, and date in a document. In this study, we focus on bank documents written in Turkish and propose a Conditional Random Fields (CRF) model to extract named entities. The main contribution of this study is twofold: (i) we propose domain-specific features to extract entity names such as law, regulation, and reference which frequently appear in bank documents; and (ii) we contribute to NER research in Turkish document which is not as mature as other languages such as English and German. Experimental results based on 10-fold cross validation conducted on 551 real-life, anonymized bank documents show the proposed CRF-NER model achieves 0.962 micro average F1 score. More specifically, F1 score for the identification of law names is 0.979, regulation name is 0.850, and article no is 0.850.

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