ORGANISATION

KisanVaani Agriculture QA

An English-language agricultural question-answer dataset containing 22,615 curated question-answer pairs covering diverse farming topics for question answering and agricultural NLP applications.

About Dataset

KisanVaani Agriculture QA is a curated question-answering dataset consisting of 22,615 English question-answer pairs covering a broad range of agricultural topics, including crop production, soil management, animal husbandry, and farming practices. It is intended to support question answering, information retrieval, conversational AI, retrieval-augmented generation (RAG), large language models, and other natural language processing applications in agriculture. This dataset was identified and facilitated for onboarding as part of the Dataset Onboarding Support Team (DOST) initiative led by CivicDataLab (CDL), partnering with the Gates Foundation in collaboration with BHASHINI. CivicDataLab provided support for dataset discovery, validation, metadata preparation and onboarding facilitation. All dataset ownership and intellectual property rights remain with the original author(s)

Purpose of Dataset

The Purpose Of This Dataset Is To Support Agricultural Question Answering, Information Retrieval, Conversational Ai, Retrieval-augmented Generation, And Natural Language Processing Research. It Enables The Development Of Intelligent Systems That Provide Accurate Agricultural Information And Decision Support For Farming-related Queries.

Dataset Metadata

License

Apache 2.0

Geographical coverage

India

Sector

AgriKosh

Author

Mohammed Ashraf

Source Organisation

Digital India BHASHINI Division

Uploaded by

Nikil Augustine

Data Quality Score (Beta)

Dataset type

Structured

Frequency

Static

Time Granularity

Year range

N.A.

Date & Time

24/08/26 12:28:25

Visibility

Open

Hosted / Redirected

Hosted

Data Type

Secondary

Data Collection Method

The Dataset Was Compiled By Collecting Agriculture-related Question-answer Pairs From Various Online Agricultural Resources, Including Agricultural Websites, Discussion Forums, And Faq Sections To Provide Reliable Domain-specific Knowledge For Agricultural Information Systems. The Collected Question-answer Pairs Were Cleaned, Standardized, And Organized Into A Structured Dataset Containing Question And Answer Fields And Were Were Manually Curated And Verified To Ensure The Quality, Accuracy, And Relevance Of The Question-answer Pairs.