Triple

T8257389
Position Surface form Disambiguated ID Type / Status
Subject John Vorster Square E193103 entity
Predicate locatedIn P40 FINISHED
Object Johannesburg E16031 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: Johannesburg | Statement: [John Vorster Square, locatedIn, Johannesburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Johannesburg
Context triple: [John Vorster Square, locatedIn, Johannesburg]
  • A. Johannesburg, South Africa chosen
    Johannesburg, South Africa is the country’s largest city and economic hub, known for its role in the gold mining industry and as a major urban center in Gauteng province.
  • B. Cape Town
    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.
  • C. Tshwane
    Tshwane is a major metropolitan area in South Africa that includes the country’s administrative capital, Pretoria, and serves as an important political and economic hub.
  • D. Pretoria, South Africa
    Pretoria, South Africa is one of the country’s three capital cities, serving as the administrative capital and a major center for government, education, and culture.
  • E. Durban
    Durban is a major coastal city in South Africa known for its busy port, subtropical climate, and significant Indian community.
  • 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_69ca82dfad9c8190b8cd18fb89f50f40 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb78fce9308190ac36512e80b06b52 completed March 31, 2026, 7:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69cebb26dd048190bd7e4de4ae986b32 completed April 2, 2026, 6:53 p.m.
Created at: March 30, 2026, 5:49 p.m.