Triple

T19420586
Position Surface form Disambiguated ID Type / Status
Subject Orange Free State Province E485840 entity
Predicate containsCity P294 FINISHED
Object Kroonstad NE NERFINISHED

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: Kroonstad | Statement: [Orange Free State Province, containsCity, Kroonstad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kroonstad
Context triple: [Orange Free State Province, containsCity, Kroonstad]
  • A. Kroonstad chosen
    Kroonstad is a town in the Free State province of South Africa, known as an agricultural and transport hub along the Vaal River.
  • B. Uitenhage
    Uitenhage is a South African town in the Eastern Cape known historically for its automotive industry and as part of the greater Port Elizabeth (Gqeberha) urban area.
  • C. 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.
  • D. Klerksdorp
    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.
  • E. Pietersburg
    Pietersburg is the former name of Polokwane, a major city and administrative center in South Africa’s Limpopo province.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8d688f881909c85104a62e09d8a completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e63214d768819082129100d7116521 completed April 20, 2026, 2:03 p.m.
Created at: April 10, 2026, 1:37 p.m.