Triple

T2435652
Position Surface form Disambiguated ID Type / Status
Subject North West E52953 entity
Predicate hasCity P316 FINISHED
Object Klerksdorp E270746 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: Klerksdorp | Statement: [North West, hasCity, Klerksdorp]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Klerksdorp
Context triple: [North West, hasCity, Klerksdorp]
  • A. Klerksdorp chosen
    Klerksdorp is a historic mining and agricultural city in South Africa’s North West Province, known as one of the country’s oldest European settlements and a regional economic hub.
  • B. Krugersdorp
    Krugersdorp is a historic mining town in South Africa known for its gold deposits and location on the West Rand of the Gauteng province.
  • C. Ermelo
    Ermelo is a key agricultural and transport hub town located in South Africa’s Mpumalanga province.
  • D. Paarl
    Paarl is a historic town in South Africa renowned for its wine estates, scenic granite rock formations, and role in the development of the Afrikaans language.
  • E. 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.
  • 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_69ab4959bcc0819083246f9fb10439e3 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abc9cd49b48190bff10a5ab7cef483 completed March 7, 2026, 6:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69af8376d6dc81909bf1e5caefb304ef completed March 10, 2026, 2:35 a.m.
Created at: March 6, 2026, 9:43 p.m.