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README.md

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+```Pages:``` 1,438,332
+```Tokens:``` 277,445,818
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 # A Curated Research Corpus for Agricultural Advisory AI Applications
 This dataset represents a comprehensive collection of 43,745 agricultural research publications from [CGIAR](https://cgiar.org/),
 specifically processed and structured for Large Language Model (LLM) applications in agricultural advisory services. 
 This dataset bridges the gap between advanced agricultural research and field-level advisory needs, 
 drawing from CGIAR's extensive scientific knowledge base that has been used by both public and private extension services. 
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+It consists of ```1,438,332``` pages of curated content, covering diverse topics such as crop science, 
+soil health, pest management, sustainable farming practices, agribusiness, and emerging agricultural technologies.
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+With a total of ```277,445,818``` tokens, this corpus provides a vast and detailed knowledge base, enabling advanced AI models to generate accurate, 
+context-aware responses for research, decision-making, and innovation in agriculture. 
+Whether for automated knowledge retrieval, chatbot development, or scientific analysis, this dataset serves as a robust foundation for AI-driven advancements in the agricultural domain.
+
 Each document has been systematically processed using [GROBID](https://grobid.readthedocs.io/en/latest/Introduction/) to extract 
 structured content while preserving critical scientific context, metadata, and domain-specific agricultural knowledge. Morever, chunking
 methods that preserver the semantic coherence have been applied. More specifically, documents are split