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
5750
Output Tokens
521
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 due to her acute community-acquired pneumonia, which required urgent hospital admission, IV antibiotics, and oxygen support after rapid deterioration. Her condition posed a higher immediate risk compared to Oscar Jansson's mild persistent asthma, which was managed effectively with outpatient treatment.