References & Citations
Computer Science > Computation and Language
Title: Fine-tuning Pre-trained Named Entity Recognition Models For Indian Languages
(Submitted on 8 May 2024 (v1), last revised 10 May 2024 (this version, v2))
Abstract: Named Entity Recognition (NER) is a useful component in Natural Language Processing (NLP) applications. It is used in various tasks such as Machine Translation, Summarization, Information Retrieval, and Question-Answering systems. The research on NER is centered around English and some other major languages, whereas limited attention has been given to Indian languages. We analyze the challenges and propose techniques that can be tailored for Multilingual Named Entity Recognition for Indian Languages. We present a human annotated named entity corpora of 40K sentences for 4 Indian languages from two of the major Indian language families. Additionally,we present a multilingual model fine-tuned on our dataset, which achieves an F1 score of 0.80 on our dataset on average. We achieve comparable performance on completely unseen benchmark datasets for Indian languages which affirms the usability of our model.
Submission history
From: Pruthwik Mishra [view email][v1] Wed, 8 May 2024 05:54:54 GMT (8155kb,D)
[v2] Fri, 10 May 2024 12:57:50 GMT (8136kb,D)
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