Triple

T8080403
Position Surface form Disambiguated ID Type / Status
Subject Department of Health (South Africa) E188598 entity
Predicate headquartersLocation P62 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: [Department of Health (South Africa), headquartersLocation, Pretoria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pretoria
Context triple: [Department of Health (South Africa), headquartersLocation, 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. Pietersburg
    Pietersburg is the former name of Polokwane, a major city and administrative center in South Africa’s Limpopo province.
  • D. 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.
  • E. Potchefstroom
    Potchefstroom is a historic university town in South Africa known for its academic institutions, military base, and role in the North West province’s agriculture and industry.
  • 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_69ca82b662e88190b9323daab8c28a21 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb40a504d48190ace96e814d99b182 completed March 31, 2026, 3:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69cde6f2bf388190ad3849317659756e completed April 2, 2026, 3:48 a.m.
Created at: March 30, 2026, 5:28 p.m.