Naamapadam
Introduced by Mhaske et al. in Naamapadam: A Large-Scale Named Entity Annotated Data for Indic Languages
Naamapadam is a Named Entity Recognition (NER) dataset for the 11 major Indian languages from two language families. In each language, it contains more than 400k sentences annotated with a total of at least 100k entities from three standard entity categories (Person, Location and Organization) for 9 out of the 11 languages. The training dataset has been automatically created from the Samanantar parallel corpus by projecting automatically tagged entities from an English sentence to the corresponding Indian language sentence.
Source: Naamapadam: A Large-Scale Named Entity Annotated Data for Indic LanguagesPapers
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