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

7771

Output Tokens

310

Cost

$0.00

Context

Input

Return the Re-examination of the patient admitted to the hospital 2025-05-20 at 09.10

Expected output

Temperature: 38.8°C, Pulse: 102 bpm, Respiratory Rate: 22/min, O2 Sat: 93% (room air), BP: 114/68, Appearance: Pale, visibly unwell, clutching left side with each cough, Auscultation: Clear crackles LLL (Left Lower Lobe), slightly diminished breath sounds in same area, Percussion: Dullness confirmed, CRP: 98 mg/L, CBC:, WBC: 13.7 x10⁹/L (elevated), Neutrophils: 9.6 x10⁹/L, ECG: Sinus tachycardia, no ischemia, Chest X-ray (STAT reading):, Infiltrate in left lower lobe, mild pleural effusion, Consistent with community-acquired pneumonia

Model output

There is no record of a patient being admitted to the hospital on 2025-05-20 at 09:10. The journal shows that Melisa Farrow had a re-examination at 09:10 on 2025-05-20 at Danderyds Vårdcentral (not a hospital admission), and she was subsequently admitted to Danderyds Sjukhus at 10:15 AM. Oscar Jansson, the other patient in the journal, was never admitted to a hospital - his case was managed entirely through outpatient consultations.