Triple

T2709159
Position Surface form Disambiguated ID Type / Status
Subject Randburg E59814 entity
Predicate adjacentTo P224 FINISHED
Object Roodepoort E59864 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: Roodepoort | Statement: [Randburg, adjacentTo, Roodepoort]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Roodepoort
Context triple: [Randburg, adjacentTo, Roodepoort]
  • A. Roodepoort chosen
    Roodepoort is a suburban city on the western side of Johannesburg in South Africa, known for its residential areas, shopping centers, and proximity to the Witwatersrand hills.
  • 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. Boksburg
    Boksburg is an industrial and residential city on the East Rand in Gauteng, South Africa, historically known for its coal mining and proximity to Johannesburg.
  • 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_69ab4ac92a088190bc74bca14038e3de completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abda7542548190bbf6c947145f7f63 completed March 7, 2026, 7:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69afaf7f99508190acfd00baec64b7e9 completed March 10, 2026, 5:43 a.m.
Created at: March 6, 2026, 9:55 p.m.