Triple

T8460946
Position Surface form Disambiguated ID Type / Status
Subject Grey College, Bloemfontein E200036 entity
Predicate city P40 FINISHED
Object Bloemfontein E24732 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: Bloemfontein | Statement: [Grey College, Bloemfontein, city, Bloemfontein]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bloemfontein
Context triple: [Grey College, Bloemfontein, city, Bloemfontein]
  • A. Bloemfontein chosen
    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. 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.
  • C. Pietersburg
    Pietersburg is the former name of Polokwane, a major city and administrative center in South Africa’s Limpopo province.
  • D. Witbank
    Witbank is a South African coal-mining city in Mpumalanga province, now officially known as Emalahleni.
  • E. Kroonstad
    Kroonstad is a town in the Free State province of South Africa, known as an agricultural and transport hub along the Vaal River.
  • 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_69ca83198c4c8190a337bf717d1813f5 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe4a0ff4c8190b17bbd33db632cea completed March 31, 2026, 3:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf8889ddcc81909ca45ce6438e3a2b completed April 3, 2026, 9:29 a.m.
Created at: March 30, 2026, 6:10 p.m.