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

14s

Input Tokens

7853

Output Tokens

468

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

Based on the patient journals provided, Melisa Farrow made a phone call to the clinic on 2025-05-20 at 08:12. However, it should be noted that she spoke with a nurse rather than directly with a doctor.

Melisa's symptoms reported during that phone call were:
- Feeling worse after waking up
- Chills
- Increased pain when breathing
- Left side aching when coughing
- Dizziness
- Fever of 38.5°C

These symptoms represented a deterioration from her initial consultation, where she had presented with a cough, chest pain when lying down (described as pressure, worse with coughing), and mild shortness of breath after walking up stairs quickly. The phone call led to an immediate urgent care appointment, where she was subsequently diagnosed with acute community-acquired pneumonia and admitted to the hospital.