Triple

T4718131
Position Surface form Disambiguated ID Type / Status
Subject North West Province E104698 entity
Predicate largestCity P235 FINISHED
Object Rustenburg E132540 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: Rustenburg | Statement: [North West Province, largestCity, Rustenburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rustenburg
Context triple: [North West Province, largestCity, Rustenburg]
  • A. Rustenburg chosen
    Rustenburg is a city in South Africa’s North West Province known for its mining industry and as one of the venues for the 2010 FIFA World Cup.
  • B. Randburg
    Randburg is a residential and commercial suburb in the north of Johannesburg, South Africa, known for its shopping centers, business districts, and leafy neighborhoods.
  • C. Mogoditshane
    Mogoditshane is a rapidly growing suburban township located just outside Botswana’s capital, Gaborone.
  • D. Graskop
    Graskop is a small tourist town in northeastern South Africa known as a gateway to the Panorama Route and nearby natural attractions like waterfalls and the Blyde River Canyon.
  • E. Bothasig
    Bothasig is a residential suburb in the northern part of Cape Town, South Africa.
  • 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_69bd43ec4a348190bc41afae43375e71 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd64261af08190b0d5d86b0e7bacc0 completed March 20, 2026, 3:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69be39f7316c8190a6ecd65b707d3fbe completed March 21, 2026, 6:25 a.m.
Created at: March 20, 2026, 1:18 p.m.