Triple

T18568362
Position Surface form Disambiguated ID Type / Status
Subject Hoërskool Pietersburg E453813 entity
Predicate locatedIn P40 FINISHED
Object Polokwane NE NERFINISHED

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: Polokwane | Statement: [Hoërskool Pietersburg, locatedIn, Polokwane]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Polokwane
Context triple: [Hoërskool Pietersburg, locatedIn, Polokwane]
  • A. Polokwane chosen
    Polokwane is a city in South Africa’s Limpopo province that served as one of the venues for matches during the 2010 FIFA World Cup.
  • B. Mthatha
    Mthatha is a town in South Africa known as a regional economic and administrative center in the Eastern Cape and as the birthplace of Nelson Mandela.
  • C. Mbombela
    Mbombela is a city in northeastern South Africa that serves as a regional economic and administrative hub near the border with Mozambique.
  • D. Mogoditshane
    Mogoditshane is a rapidly growing suburban township located just outside Botswana’s capital, Gaborone.
  • E. Mogale City
    Mogale City is a local municipality in Gauteng, South Africa, that includes the town of Krugersdorp and surrounding areas on the West Rand.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d38974308190a9174430ef256b73 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e53affc3e08190b4d16b5ccb0bddbc completed April 19, 2026, 8:28 p.m.
Created at: April 10, 2026, 11:43 a.m.