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

Input Tokens

5951

Output Tokens

442

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 is the patient who spoke with the doctor over the phone. She reported chills, a worsening cough, left‑side chest pain that intensified when she coughed, a fever of 38.5 °C, and a feeling of dizziness.