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Title: Named Entity Recognition For Macedonian Language
Authors: Gramatikov, Sasho 
Mirchev, Miroslav 
Mishkovski, Igor 
Ivan Krstev
Fisnik Doko
Keywords: NER, Entity Recognition, FLAIR, NLP, Machine Learning
Issue Date: 6-May-2021
Publisher: CIIT 2021
Project: Разбирање на природни јазици во информации од вести преку користење на Трансформер архитектурата и каузални декодери
Conference: 18th International Conference on Informatics and Information Technologies
Abstract: Named Entity Recognition (NER), an outstanding technique for information extraction from unstructured texts, is lately becoming the central problem in the field of Natural Language Processing (NLP). In the last few years, multiple Python libraries, like SpaCy, NLTK and FLAIR, accomplished state-of-the-art performances for this problem. As NER is developing into a powerful technique, its real-live applications are becoming more and more numerous: from customer-message categorization to ease of document analysis in greater corporations. In this research, we use a ML-based system with the help of the FLAIR library in Python, which has already provided optimal results for NER in few world-class languages (English, German, Russian, French etc.), for financial entity recognition in financial texts written in Macedonian language. For the NER task on 13 distinct labels using our dataset in Macedonian language on the proposed ML model we have obtained F1-score of around 0.75.
Appears in Collections:Faculty of Computer Science and Engineering: Conference papers

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