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
11s
Input Tokens
7756
Output Tokens
445
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. She was a 39-year-old teacher who initially presented with what seemed like a mild cough and chest pain, but her condition deteriorated overnight. She developed fever (38.8°C), increased respiratory rate, decreased oxygen saturation (93%), and was diagnosed with community-acquired pneumonia in the left lower lobe with pleural effusion. Due to her worsening symptoms and need for IV antibiotics and oxygen support, she was admitted to Danderyds Sjukhus Internal Medicine Ward for inpatient treatment.