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.

0
Duration
3s
Input Tokens
6700
Output Tokens
452
Cost
$0.00
Context
Input
Which patient had to be accepted in the hospital?
Expected output
Melisa Farrow
Model output
Melisa Farrow (39 years old) had to be accepted in the hospital due to diagnosed community-acquired pneumonia (CAP) in the left lower lobe, confirmed by chest X-ray and elevated CRP levels.