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.

100
Duration
42s
Input Tokens
7755
Output Tokens
396
Cost
$0.00
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 Jansson developed mild asthma that was managed successfully as an outpatient, Melisa developed community-acquired pneumonia that rapidly deteriorated within 24 hours, requiring hospitalization. Her oxygen levels dropped to 93%, she needed IV antibiotics and supplemental oxygen, and she spent 3 days in the hospital. The combination of her initial symptom minimization and the infection's rapid progression made her condition potentially life-threatening without prompt intervention.