silpa_nlp at SemEval-2022 Tasks 11: Transformer based NER models for Hindi and Bangla languages

2022-07-01 · SemEval (NAACL) 2022 7 · Sumit Singh, Pawankumar Jawale, Uma Tiwary

We present Transformer based pretrained models, which are fine-tuned for Named Entity Recognition (NER) task. Our team participated in SemEval-2022 Task 11 MultiCoNER: Multilingual Complex Named Entity Recognition task for Hindi and Bangla. Result comparison of six models (mBERT, IndicBERT, MuRIL (Base), MuRIL (Large), XLM-RoBERTa (Base) and XLM-RoBERTa (Large) ) has been performed. It is found that among these models MuRIL (Large) model performs better for both the Hindi and Bangla languages. Its F1-Scores for Hindi and Bangla are 0.69 and 0.59 respectively.

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Tasks

named-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)NER

LLM-RM at SemEval-2023 Task 2: Multilingual Complex NER using XLM-RoBERTa

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Named Entity Recognition(NER) is a task of recognizing entities at a token level in a sentence. This paper focuses on solving NER tasks in a multilingual setting for complex named entities. Our team, LLM-RM participated …

named-entity-recognition Named Entity Recognition Named Entity Recognition (NER)NER+2

SemEval-2022 Task 11: Multilingual Complex Named Entity Recognition (MultiCoNER)

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named-entity-recognition Named Entity Recognition Named Entity Recognition (NER)NER

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2020-05-01 · LREC 2020 5 · Arup Baruah, Kaushik Das, Ferdous Barbhuiya, Kuntal Dey

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Aggression Identification Misogynistic Aggression Identification

FastPOS: Language-Agnostic Scalable POS Tagging Framework Low-Resource Use Case

2025-11-30 · Md Abdullah Al Kafi, Sumit Kumar Banshal arxiv

This study proposes a language-agnostic transformer-based POS tagging framework designed for low-resource languages, using Bangla and Hindi as case studies. With only three lines of framework-specific code, the model was…

POS Tagging

SemEval-2023 Task 2: Fine-grained Multilingual Named Entity Recognition (MultiCoNER 2)

2023-05-11 · Besnik Fetahu, Sudipta Kar, Zhiyu Chen, Oleg Rokhlenko 외

We present the findings of SemEval-2023 Task 2 on Fine-grained Multilingual Named Entity Recognition (MultiCoNER 2). Divided into 13 tracks, the task focused on methods to identify complex fine-grained named entities (li…

Multilingual Named Entity Recognition named-entity-recognition Named Entity Recognition NER+1