Tests a model's basic world model and ability to track object state through simple riddles presented in multiple languages. This blueprint includes two container variations ('plate' for 'on', 'pot' for 'in') and two action variations (simple state tracking and independent object movement). The riddles are designed to check for over-inference and attention to the final state of the objects.

Comparing human judgements vs LLM judges on Claude Opus 4.5 and Sonnet 4.5 responses to legal and agriculture questions in 7 Indian languages.

Human ratings from Karya platform (native speaker evaluators) are stored separately for comparison with LLM judge scores.

Prompts: 9293 Languages: Hindi, Bengali, Telugu, Kannada, Malayalam, Assamese, Marathi Domains: Legal, Agriculture Human evaluators: ~120 native speakers

Pilot evaluation comparing human judgements vs LLM judges on multilingual AI responses.

This blueprint tests Claude Opus 4.5 and Sonnet 4.5 responses to legal and agriculture questions in 5 Indian languages (Hindi, Bengali, Telugu, Malayalam, Kannada). The rubric criteria are adapted from Karya's human evaluation dimensions:

• Fluency: Is the language natural and readable?
• Complexity: Is the language appropriate (neither too complex nor too simplistic)?
• Code-switching: Is the use of English words balanced and helpful?
• Trustworthiness: Does the response provide accurate, actionable information?

Source: Karya platform evaluation data (10,000+ human evaluations from native speakers). Human ratings are available for comparison but not included in this blueprint.

Note: This is a 5-sample pilot to test the methodology before full-scale integration.