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

27s

Input Tokens

2771

Output Tokens

335

Cost

$0.00

Context

Input

Order all the cities named in the text by time of visiting them

Expected output

1.Cartagena (14 Jun 1995) 2.Leticia (mid-Jun 1995, the day after Cartagena) 3.Manchester (3 Oct 2002 entry) 4.Tangier (mid-Apr 2004, one week before 22 Apr) 5.Chefchaouen (mid-Apr 2004, just after Tangier) 6.Granada (22 Apr 2004) 7.Córdoba 8.Sevilla 9.Cádiz 10.Málaga 11.Jaén 12.Toledo 13.Madrid 14.Ávila 15.Salamanca 16.Zamora 17.San Sebastián 18.Bilbao (8 May 2004)

Model output

The cities mentioned in the text, ordered by the time they were visited, are:

1. Cartagena, Colombia
2. Leticia, Colombia (planned immediately after Cartagena)
3. Chefchaouen, Morocco (visited before arriving in Spain, just before Granada)
4. Granada, Spain
5. Córdoba, Spain
6. Sevilla, Spain
7. Cádiz, Spain
8. Málaga, Spain
9. Jaén, Spain
10. Toledo, Spain
11. Madrid, Spain
12. Ávila, Spain
13. Salamanca, Spain
14. Zamora, Spain
15. San Sebastián, Spain
16. Bilbao, Spain
17. Manchester, England (home/location after prior travels)

The order is based on context clues and explicit chronological remarks in the text.