Using Stanford part-of-speech tagger for the morphologically-rich Filipino Language

• Main Authors: Go, Matthew Phillip V., Nocon, Nicco Louis S.
• Format: text
• Published: Animo Repository 2019
• Subjects: Filipino language—Parts of speech; South and Southeast Asian Languages and Societies
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/484
• Institution: De La Salle University

This research focuses on the implementation of a Maximum Entropy-based Part-of-Speech (POS) tagger for Filipino. It uses the Stanford POS tagger - a trainable POS tagger that has been trained on English, Chinese, Arabic, and other languages and producing one of the highest results in each language....