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
3s
Input Tokens
6700
Output Tokens
374
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 in the hospital due to confirmed community-acquired pneumonia (left lower lobe) and associated complications.