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.

Duration

23s

Input Tokens

7762

Output Tokens

253

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 talked on the phone with a nurse on May 20, 2025. Her symptoms at the time of the call included: chills, increased pain when breathing, aching in her left side when coughing, dizziness, and a fever of 38.5°C. She had initially presented the day before with what she thought was a minor cough and chest pain, but her condition had deteriorated overnight, prompting the urgent phone call and immediate visit to the clinic.