Abstract
Named Entity Recognition (NER) is the process of automatic extraction of Named Entities (NEs) by means of recognizing (finding the entities in a given text) and their classification (assigning a type). A lot of work has been done in English and other languages for NER but very little research has been done for Nepali NER. Nepali language has its own issues and challenges which need to be addressed. In this paper, we present the NE Tagset and features that can be potentially used for Nepali NER. To train the model classifiers like Support Vector Machine (SVM), Multinomial Naïve Bayes and Logistic Regression are used and their precision, recall and F1-score have been calculated. 5 fold cross validation is used to evaluate and validate our model.
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Maharjan, G., Bal, B.K., Regmi, S. (2019). Named Entity Recognition (NER) for Nepali. In: Kravets, A., Groumpos, P., Shcherbakov, M., Kultsova, M. (eds) Creativity in Intelligent Technologies and Data Science. CIT&DS 2019. Communications in Computer and Information Science, vol 1084. Springer, Cham. https://doi.org/10.1007/978-3-030-29750-3_6
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DOI: https://doi.org/10.1007/978-3-030-29750-3_6
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