Opper

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.

Context Reasoning – anthropic/claude-3.5-haiku Task | Opper AI

Input Tokens

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Output Tokens

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Duration

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Cost

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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

Based on the text, the cities can be ordered chronologically as follows:

1. Cartagena, Colombia (June 14, 1995)
2. Chefchaouen, Morocco (mentioned before arriving in Granada)
3. Granada, Spain (April 22, 2004)
4. Córdoba, Spain (mentioned after Granada)
5. Sevilla, Spain
6. Cádiz, Spain
7. Málaga, Spain
8. Jaén, Spain
9. Toledo, Spain
10. Madrid, Spain
11. Ávila, Spain
12. Salamanca, Spain
13. Zamora, Spain
14. San Sebastián, Spain
15. Bilbao, Spain (May 8, 2004)
16. Manchester, England (October 3, 2002 - mentioned as home, not a travel destination)

The traveler visited these cities during his travels in Spain, with additional context from visits to Colombia and Morocco.