mlsanityData to 7 Oct 2026

L3Cube-MahaNER: A Marathi Named Entity Recognition Dataset and BERT models

arXiv 2204.06029 ↗First posted 12 Apr 2022cs.CL cs.LGcited by 21

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Abstract (arXiv)

Named Entity Recognition (NER) is a basic NLP task and finds major applications in conversational and search systems. It helps us identify key entities in a sentence used for the downstream application. NER or similar slot filling systems for popular languages have been heavily used in commercial applications. In this work, we focus on Marathi, an Indian language, spoken prominently by the people of Maharashtra state. Marathi is a low resource language and still lacks useful NER resources. We present L3Cube-MahaNER, the first major gold standard named entity recognition dataset in Marathi. We also describe the manual annotation guidelines followed during the process. In the end, we benchmark the dataset on different CNN, LSTM, and Transformer based models like mBERT, XLM-RoBERTa, IndicBERT, MahaBERT, etc. The MahaBERT provides the best performance among all the models. The data and models are available at https://github.com/l3cube-pune/MarathiNLP .

Key facts. Cited by 21 papers in the map (data through 7 Oct 2026). Builds on 11 of its 33 references that are in the map. First posted on arXiv 12 Apr 2022.

Builds on

11 of 33 references.

References · 11

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,266
  3. 2019ALBERT: A Lite BERT for Self-supervised Learning of Language Representationscited by 2,772
  4. 2019How multilingual is Multilingual BERT?cited by 642
  5. 2016Neural Architectures for Named Entity Recognitioncited by 548
  6. 2019A Survey on Recent Advances in Named Entity Recognition from Deep Learning modelscited by 117
  7. 2022L3Cube-MahaCorpus and MahaBERT: Marathi Monolingual Corpus, Marathi BERT Language Models, and Resourcescited by 49
  8. 2021L3CubeMahaSent: A Marathi Tweet-based Sentiment Analysis Datasetcited by 28
  9. 2020Deep Learning for Hindi Text Classification: A Comparisoncited by 22
  10. 2021Experimental Evaluation of Deep Learning models for Marathi Text Classificationcited by 19
  11. 2021Hate and Offensive Speech Detection in Hindi and Marathicited by 17

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 3; 2023: 8; 2024: 4; 2025: 1; 2026: 5.

21 papers.

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  1. 2022L3Cube-HindBERT and DevBERT: Pre-Trained BERT Transformer models for Devanagari based Hindi and Marathi Languagescited by 35
  2. 2022L3Cube-MahaNLP: Marathi Natural Language Processing Datasets, Models, and Librarycited by 30
  3. 2022Naamapadam: A Large-Scale Named Entity Annotated Data for Indic Languagescited by 28
  4. 2024Sebastian, Basti, Wastl?! Recognizing Named Entities in Bavarian Dialectal Datacited by 8
  5. 2023L3Cube-MahaSent-MD: A Multi-domain Marathi Sentiment Analysis Dataset and Transformer Modelscited by 6
  6. 2024Can LLM Substitute Human Labeling? A Case Study of Fine-grained Chinese Address Entity Recognition Dataset for UAV Deliverycited by 5
  7. 2023Breaking Language Barriers: A Question Answering Dataset for Hindi and Marathicited by 4
  8. 2023mahaNLP: A Marathi Natural Language Processing Librarycited by 3
  9. 2023My Boli: Code-mixed Marathi-English Corpora, Pretrained Language Models and Evaluation Benchmarkscited by 2
  10. 2023Analysing Cross-Lingual Transfer in Low-Resourced African Named Entity Recognitioncited by 2
  11. 2023L3Cube-MahaSocialNER: A Social Media based Marathi NER Dataset and BERT modelscited by 2
  12. 2024OpenNER 1.0: Standardized Open-Access Named Entity Recognition Datasets in 50+ Languagescited by 2
9 more
  1. 2024MahaSQuAD: Bridging Linguistic Divides in Marathi Question-Answeringcited by 1
  2. 2025TriNER: A Series of Named Entity Recognition Models For Hindi, Bengali & Marathicited by 1
  3. 2023Enhancing Low Resource NER Using Assisting Language And Transfer Learningcited by 0
  4. 2023On Significance of Subword tokenization for Low Resource and Efficient Named Entity Recognition: A case study in Marathicited by 0
  5. 2026AWED-PIPER: Agents, Web Applications & Expert Detectors for Personally Identifiable Information Protection & Fine-grained Named Entity Recognition across 36 languages for 6.6 Billion Speakerscited by 0
  6. 2026BhashaSetu: Cross-Lingual Knowledge Transfer from High-Resource to Extreme Low-Resource Languagescited by 0
  7. 2026L3Cube-MahaPOS: A Marathi Part-of-Speech Tagging Dataset and BERT Modelscited by 0
  8. 2026BERT-based Models vs. Large Language Models for Low-Resource Named Entity Recognition: A Comparative Study on Marathicited by 0
  9. 2026Named Entity Recognition using Sliding Window Approachcited by 0