Triple

T10766153
Position Surface form Disambiguated ID Type / Status
Subject Kirstenhof E253959 entity
Predicate locatedInAdministrativeTerritory P40 FINISHED
Object City of Cape Town E24410 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: City of Cape Town | Statement: [Kirstenhof, locatedInAdministrativeTerritory, City of Cape Town]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Cape Town
Context triple: [Kirstenhof, locatedInAdministrativeTerritory, City of Cape Town]
  • A. Cape Town chosen
    Cape Town is a major coastal city in South Africa known for its iconic Table Mountain, diverse culture, and role as the country’s legislative capital.
  • B. Hub City
    Hub City is the nickname for Hagerstown, Maryland, reflecting its historical role as a major regional transportation and commercial center.
  • C. Hub City
    Hub City is a common nickname for Moncton, a major transportation and commercial center in New Brunswick, Canada.
  • D. Hub City
    Hub City is a nickname for Colton, California, reflecting its historical role as a major regional transportation and railroad center.
  • E. Hub City
    Hub City is the nickname for Lubbock, Texas, a major economic, educational, and healthcare center for the surrounding West Texas region.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d6aa5f54f4819082d0bbcb6f8797e6 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d7322d3a9c81909e58f6064643b814 completed April 9, 2026, 4:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69e3e6d27d8c8190b2c8ee9c54cf7fd1 completed April 18, 2026, 8:17 p.m.
Created at: April 8, 2026, 9:16 p.m.