Reduplicated MWE (RMWE) helps in improving the CRF based Manipuri POS Tagger

TL;DR

This paper enhances Manipuri POS tagging by incorporating Reduplicated Multiword Expressions (RMWE) as features in a CRF model, significantly improving tagging accuracy.

Contribution

The study introduces RMWE as a novel feature in CRF-based POS tagging for Manipuri, demonstrating improved performance over previous methods.

Findings

Recall improved to 80.20% with RMWE

Precision increased to 74.31% with RMWE

F-measure reached 77.14% with RMWE

Abstract

This paper gives a detail overview about the modified features selection in CRF (Conditional Random Field) based Manipuri POS (Part of Speech) tagging. Selection of features is so important in CRF that the better are the features then the better are the outputs. This work is an attempt or an experiment to make the previous work more efficient. Multiple new features are tried to run the CRF and again tried with the Reduplicated Multiword Expression (RMWE) as another feature. The CRF run with RMWE because Manipuri is rich of RMWE and identification of RMWE becomes one of the necessities to bring up the result of POS tagging. The new CRF system shows a Recall of 78.22%, Precision of 73.15% and F-measure of 75.60%. With the identification of RMWE and considering it as a feature makes an improvement to a Recall of 80.20%, Precision of 74.31% and F-measure of 77.14%.