Developing an unsupervised grammar checker for Filipino using hybrid n-grams as grammar rules

This study focuses on using hybrid n-grams as grammar rules for detecting grammatical errors and providing corrections in Filipino. These grammar rules are derived from grammatically-correct and tagged texts which are made up of part-of-speech (POS) tags, lemmas, and surface words sequences. Due to the structure of the rules used by this system, it presents an opportunity to have an unsupervised grammar checker for Filipino when coupled with existing POS taggers and morphological analyzers. The approach is also customized to cover different error types present in the Filipino language. The system achieved 82% accuracy when tested on checking erroneous and error-free texts