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Description
IndianCRIC is an Indian Climate Resilience Instruction Corpus built for the Adaption Labs Uncharted Data Challenge 2026. The dataset contains genuine and scam instruction pairs in five languages, focusing on vulnerable populations in Bihar, Uttar Pradesh, and Jharkhand. It was created by sahilmaniyar888 and last updated on April 30, 2026.
Use Cases
Train models to detect climate-related misinformation based on the described genuine vs. scam instruction pairs.
Develop multilingual NLP systems for climate resilience communication based on the five languages mentioned.
Analyze scam patterns in extreme weather events based on the described fake helplines and fraudulent relief schemes.
Build instruction-following AI assistants for vulnerable regions based on the corpus of structured instructions.
Strengths
Contains parallel data in five languages, which may support multilingual model training.
Includes genuine and scam instruction pairs, providing a direct comparison for analysis.
Focuses on a specific, high-impact geographic region (Bihar, Uttar Pradesh, and Jharkhand).
Created for a named challenge (Adaption Labs Uncharted Data Challenge 2026), suggesting a defined purpose.
Limitations
Column-level documentation is absent; field semantics must be inferred after download.
Row count and dataset size are unknown, which may limit suitability assessment.
The description metadata is limited; actual data quality requires manual inspection after download.
Provenance
Source
huggingface
Collection Method
Built for the Adaption Labs Uncharted Data Challenge 2026; specific collection method is not detailed.
Time Range
Temporal coverage is not specified.
Freshness
Last updated 2026-04-30 13:18:12; freshness should be verified.
Geography
Focuses on vulnerable populations in the Indian states of Bihar, Uttar Pradesh, and Jharkhand.
License is unknown; users should verify permissions before use.