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
12s
Input Tokens
7380
Output Tokens
134
Cost
$0.00
Context
Input
Which patient talked on the phone with a doctor, and what were their symptoms?
Expected output
Melisa Farrow, who had 38.5°C fever, cough, her left side hurts, has pain when breathing and feels dizzy
Model output
Melisa Farrow called the clinic on 2025-05-20 and reported chills, increased breathing difficulty, chest pain, and dizziness. She had a fever of 38.5°C.