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
25s
Input Tokens
5881
Output Tokens
683
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 because her pneumonia required hospitalization, IV antibiotics, and oxygen support, whereas Oscar’s mild asthma was largely managed on an outpatient basis.