Question and Answer pairs with relevance to livestock-based agriculture in the Global South

Version 2.0
Domelevo Entfellner, Jean-Baka; Dhulipala, Ram; Kihoro, Esther; Korir, Max; Anyona, Beatrice; Kone Galgallo, Diba; Sharma, Garima; Njoki Nganga, Irene; Lepariyo, Watson; Kiptanui, Ken; Ojanji, Wandera; Ndirangu, Esther; Cherotich, Fredah; Juma, John; Mwangi Gituma, Michael; Kamau, Mwangi; Kramer, Berber; Boukaka, Sedi; Richards, Shauna; Karugia, Joseph; Patel, Ekta; Chebet, Arusey; Mware, Bernard; Wanjawa, Barack; Ronoh, Nathan; Okoma, Sheila; Malicha, Wario; Webi, Ethel; Lukuyu, Ben; Rutto, Erick; Njamba, Harrison, 2025, "Question and Answer pairs with relevance to livestock-based agriculture in the Global South", https://hdl.handle.net/20.500.11766.1/FK2/6U4UAI, MELDATA, V2
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Description
This crowdsourced dataset comprises a set of two comma separated values (CSV) files. The first one is the set of 598 rows corresponding to questions, some of which are answered (with some of the answers being accompanied by source references). The second file is the subset of the 312 questions and answer pairs with non-null answers. This dataset was collected at the International Livestock Research Institute (ILRI) in Nairobi, Kenya during a hackathon organized on 09 June 2025. It can be used for the purpose of training, validating or testing an Artificial Intelligence agent. The basis for the creation of this dataset was the CGIAR-wide effort to train the AgriLLM large language model. Participants of the hackathon were ILRI staff members as well as members of institutions hosted at the ILRI campus in Nairobi.
Subject Agricultural Sciences
Keyword training, crowdsourcing, event, q/a pairs, hackathon, agrillm
Related Publication CGIAR. 2025. AgriLLM: How CGIAR is developing an AI-powered agricultural advisory service for global South. https://www.cgiar.org/news-events/news/agrillm-how-cgiar-is-developing-an-ai-powered-agricultural-advisory-service-for-global-southurl: https://www.cgiar.org/news-events/news/agrillm-how-cgiar-is-developing-an-ai-powered-agricultural-advisory-service-for-global-south
Notes Type: Dataset; Sub-type(s): Other (Hackathon output: Question and Answer pairs with relevance to agriculture)
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all_598rows_QA_hackathon_ILRI_20250609.csv
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Published Jan 29, 2026
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answered_only_312rows_QA_hackathon_ILRI_20250609.csv
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Published Jan 29, 2026
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MD5: fbc1dca8a33efc523ea70474ff111fb0
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