5 papers
Named Entity Recognition using Sliding Window Approach
Hariom Ingle, Ronit Ghode, Ishwari Gondkar +3
Named Entity Recognition (NER) is a core NLP task, but transformer-based sentence-level models struggle with long documents because of fixed input-length limits: truncation drops c…
BERT-based Models vs. Large Language Models for Low-Resource Named Entity Recognition: A Comparative Study on Marathi
Hariom Ingle, Ronit Ghode, Ishwari Gondkar +2
Named Entity Recognition (NER) for low-resource languages such as Marathi remains a challenging task due to limited annotated resources and linguistic complexity. Although recent L…
MahaParaphrase: A Marathi Paraphrase Detection Corpus and BERT-based Models
Suramya Jadhav, Abhay Shanbhag, Amogh Thakurdesai +3
Paraphrases are a vital tool to assist language understanding tasks such as question answering, style transfer, semantic parsing, and data augmentation tasks. Indic languages are c…
Non-Contextual BERT or FastText? A Comparative Analysis
Abhay Shanbhag, Suramya Jadhav, Amogh Thakurdesai +2
Natural Language Processing (NLP) for low-resource languages, which lack large annotated datasets, faces significant challenges due to limited high-quality data and linguistic reso…
On Limitations of LLM as Annotator for Low Resource Languages
Suramya Jadhav, Abhay Shanbhag, Amogh Thakurdesai +2
Low-resource languages face significant challenges due to the lack of sufficient linguistic data, resources, and tools for tasks such as supervised learning, annotation, and classi…