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Benchmarking Mi-NER: Malay Entity Recognition Engine

Authors:
Thenmalar Ulanganathan
Ali Ebrahimi
Benjamin Chu Min Xian
Khalil Bouzekri
Rohana Mahmud
Ong Hong Hoe

Keywords: Benchmarking; Malay Language; Natural Language Processing; Named Entity Recognition

Abstract:
Named entity recognition (NER) is a process of recognizing, identifying, and extracting useful entities, like person, location and organization for information mining from unstructured texts. This paper presents (Mi-NER), a Malay language Named Entity Recognition engine that is developed using a probabilistic approach. The results of benchmarking Mi-NER against existing systems are presented in this paper. In addition, the details of the experimental work are highlighted and discussed. Precision, Recall and F-Measure have been used to measure the results for this evaluation.

Pages: 52 to 58

Copyright: Copyright (c) IARIA, 2017

Publication date: March 19, 2017

Published in: conference

ISSN: 2308-4375

ISBN: 978-1-61208-542-5

Location: Nice, France

Dates: from March 19, 2017 to March 23, 2017