Named Entity Recognition for Nepali Language
This work addresses the lack of NER studies for the Nepali language, providing a domain-specific solution.
The paper tackles Named Entity Recognition for the Nepali language, achieving a 33% to 50% relative improvement over feature-based SVM models and up to a 10% improvement over state-of-the-art neural models for other languages.
Named Entity Recognition have been studied for different languages like English, German, Spanish and many others but no study have focused on Nepali language. In this paper we propose a neural based Nepali NER using latest state-of-the-art architecture based on grapheme-level which doesn't require any hand-crafted features and no data pre-processing. Our novel neural based model gained relative improvement of 33% to 50% compared to feature based SVM model and up to 10% improvement over state-of-the-art neural based model developed for languages beside Nepali.