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

24s

Input Tokens

6828

Output Tokens

1008

Cost

$0.00

Context

Input

Which patient had a more dangerous medical timeline?

Expected output

Melisa Farrow

Model output

Melisa Farrow had a more dangerous medical timeline.

    **Key Reasons:**
    1. **Acute, life-threatening infection** (community-acquired pneumonia with pleural effusion) vs. Oscar’s **chronic, mild asthma**.
    2. **Rapid deterioration** requiring **hospitalization, IV antibiotics, and oxygen therapy**, while Oscar was managed entirely as an outpatient.
    3. **Systemic inflammation** (high fever, CRP 98 mg/L, hypoxia) vs. Oscar’s stable vitals and mild symptoms.
    4. **Higher risk of complications** (e.g., sepsis, respiratory failure) compared to Oscar’s low-risk asthma exacerbation.

    Oscar’s condition, though requiring treatment, never posed an immediate threat to his health or required urgent intervention.