Context Reasoning – anthropic/claude-opus-4 Task | Opper AI

Context Reasoning

Context understanding and reasoning tasks test accurate answers grounded in provided context. This capability is essential for knowledge-base support bots, policy lookup systems, and internal knowledge Q&A applications. Models are evaluated on their ability to provide accurate answers that are properly grounded in the given context rather than hallucinating information.

Input Tokens

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Output Tokens

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Duration

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Cost

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Context

Input

Which patient had a more dangerous medical timeline?

Expected output

Melisa Farrow

Model output

Melisa Farrow had a more dangerous medical timeline. While Oscar's asthma was concerning, it was mild and managed entirely as an outpatient with inhaled medications. Melisa, however, developed community-acquired pneumonia that rapidly progressed within 24 hours, requiring emergency hospitalization, IV antibiotics, and oxygen support. Her condition showed systemic infection signs (high fever, elevated inflammatory markers, low oxygen saturation) and could have become life-threatening without prompt hospital treatment.