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
6s
Input Tokens
6829
Output Tokens
339
Cost
$0.00
Context
Input
Which patient had to be accepted in the hospital?
Expected output
Melisa Farrow
Model output
Melisa Farrow had to be accepted into the hospital due to worsening community-acquired pneumonia with pleuritic chest pain, confirmed by clinical deterioration (fever, hypoxia, and radiographic findings).