Using Stanford part-of-speech tagger for the morphologically-rich Filipino Language
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....
Saved in:
| Main Authors: | , |
|---|---|
| Format: | text |
| Published: |
Animo Repository
2019
|
| Subjects: | |
| Online Access: | https://animorepository.dlsu.edu.ph/faculty_research/484 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | De La Salle University |