Triple

T14016934
Position Surface form Disambiguated ID Type / Status
Subject Alexandra township E337227 entity
Predicate countryCapitalNearest P1982 FINISHED
Object Pretoria E5262 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: Pretoria | Statement: [Alexandra township, countryCapitalNearest, Pretoria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pretoria
Context triple: [Alexandra township, countryCapitalNearest, Pretoria]
  • A. Bloemfontein
    Bloemfontein is a major South African city known as the seat of the country’s highest courts and one of its three national capitals.
  • B. 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.
  • C. Johannesburg
    Johannesburg is a champion Thoroughbred racehorse and successful sire, best known for his unbeaten two-year-old season and victory in the 2001 Breeders’ Cup Juvenile.
  • D. Pietersburg
    Pietersburg is the former name of Polokwane, a major city and administrative center in South Africa’s Limpopo province.
  • E. Pretoria, South Africa chosen
    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.
  • 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_69d81c6543a48190bd5ba93d7419e797 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2f396b648190927e5718c3bb6511 completed April 14, 2026, 12:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd323e89948190bb280e93e2058c0a completed May 8, 2026, 12:45 a.m.
Created at: April 9, 2026, 10:19 p.m.