stylistic:tone
Natural language processing for Marathi

More recent attention has focused on developing natural language processing tools for Marathi. Some studies proposed a couple of text corpora for Marathi. L3CubeMahaSent is the first major publicly available Marathi dataset for sentiment analysis. It contains about 16,000 distinct tweets classified into three broad classes, such as positive, negative, and neutral. L3Cube-MahaNER is a dataset for named-entity recognition consisting of 25,000 manually tagged sentences categorised according to the eight entity classes. There are at least two public available datasets for hate speech detection in Marathi: L3Cube-MahaHate and HASOC2021.

The HASOC2021 dataset was proposed for conducting a machine learning competition on hate, offensive, and profane content identification in Marathi collocated with Forum for Information Retrieval Evaluation (FIRE 2021). The participants of the competition presented 25 solutions based on supervised learning. The winning teams used pre-trained language models (XLM-RoBERTa, Language Agnostic BERT Sentence Embeddings (LaBSE)) fine-tuned on the HASOC2021 dataset proposed by the organisers. The participants also experimented with the joint use of multilingual data for fine-tuning.