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Purpose of Dataset

This Dataset Is Designed To Enable The Development Of Multilingual Agricultural Ai Systems For India's Diverse Linguistic Landscape. It Supports Training And Fine-tuning Of Nlp, Small Language Models (Slms), And Large Language Models (Llms) For Tasks Such As Hindi-english-indic Language Agricultural Query Understanding, Semantic Video Retrieval, Metadata Enrichment, Topic Classification, Automated Tagging, Summarization, And Recommendation Engines. Researchers Can Build Agricultural Knowledge Graphs, Smart E-learning Platforms, And Ai-powered Agritech Solutions Focused On Soil Health, Sustainable Farming, Irrigation Management, And Farmer Education. The Dataset Is Also Suitable For Cross-lingual Information Retrieval, Agricultural Ontology Creation, And Domain-specific Model Evaluation. By Providing Metadata In 12+ Languages, It Directly Addresses The Language Barrier In Indian Digital Agriculture, Making Extension Content Accessible To Farmers In Their Native Tongues.