ghananlpcommunity/ghana-farmer-qa

Ghana Farmer Q&A

151,469 question-answer pairs on Ghanaian smallholder farming, grounded in 15,174 recorded interviews with Ghanaian farmers.

Every Q&A pair traces back to something a farmer actually said. The pairs are not free-floating model output about African agriculture -- each one was written against a specific interview passage, and that passage travels with it in the source_text and original_twi columns, so you can always check an answer against its source.

Where the content comes from

1. 1.Field recordings. Ghanaian farmers were recorded discussing their practice in Twi -- cocoa spacing, pest pressure, soil fertility, harvest and pricing. These were transcribed and translated into English, published as `ghananlpcommunity/twi-english-agric`.
2. 2.Question generation. For each of the 15,174 interview passages, a model (Gemini 3.6 Flash) was asked to write ~10 standalone questions a farmer might put to an extension officer about the practices described in that passage, plus an explanatory answer for each. Each question had to stand on its own -- no follow-ups, no references to "the text above" -- so the pairs are usable outside their original context.
3. 3.Flattening. One row per Q&A pair, carrying its source passage forward.

So the knowledge is farmer-sourced and the question-answer framing is model-written. That distinction matters for how you use it -- see Limitations.

Columns

Questions average 16 words, answers 34 words. Common topics include pest and disease control, soil and nutrient management, planting and spacing, crop growth and behaviour, root and tuber crops, and vegetable farming.

What it's useful for

• —Training and evaluating agricultural QA and extension-advice assistants for Ghanaian farmers, in a register that matches how farmers actually ask.
• —Instruction tuning where you want grounded, domain-specific QA rather than generic web text.
• —Retrieval and grounding research -- source_text gives every answer a provenance passage, so you can measure whether an answer is supported.
• —A seed corpus for Ghanaian-language work. Parallel Ewe, Ga and Twi versions are published separately (below).
• —Human post-editing into a reviewed, gold-standard extension corpus. This is the highest-value next step and the dataset is structured for it.

Parallel Ghanaian-language versions

• —`ghananlpcommunity/ghana-farmer-qa-ewe` -- Ewe
• —`ghananlpcommunity/ghana-farmer-qa-ga` -- Ga
• —`ghananlpcommunity/ghana-farmer-qa-twi` -- Twi

Limitations

• —The answers are model-written, not expert-reviewed. They are grounded in farmer interviews, but no agronomist verified them. Do not deploy this as extension advice without review.
• —`category` is free text, not a controlled vocabulary. The model chose a label per batch, producing ~24,000 distinct strings with heavy near-duplication ("Pest & Disease Control", "Pest and Disease Management", "Pest Management"). Cluster or remap it before using it as a label.
• —Interview coverage shapes topic coverage. Crops and regions that came up often in the recordings are well represented; others barely appear. This is not a balanced survey of Ghanaian agriculture.
• —The English passages are themselves translations from Twi speech, so transcription and translation error is upstream of everything here.

License

CC BY-NC 4.0, inherited from the source dataset `ghananlpcommunity/twi-english-agric`.