Triple

T11571356
Position Surface form Disambiguated ID Type / Status
Subject National Railways of Zimbabwe E274393 entity
Predicate headquartersLocation P62 FINISHED
Object Bulawayo E9766 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: Bulawayo | Statement: [National Railways of Zimbabwe, headquartersLocation, Bulawayo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bulawayo
Context triple: [National Railways of Zimbabwe, headquartersLocation, Bulawayo]
  • A. Bulawayo chosen
    Bulawayo is Zimbabwe’s second-largest city and a major industrial, cultural, and transport hub in the southwestern part of the country.
  • B. Manzini
    Manzini is a major city in Eswatini that serves as an important commercial and transport hub of the country.
  • C. Witbank
    Witbank is a South African coal-mining city in Mpumalanga province, now officially known as Emalahleni.
  • D. Maputo
    Maputo is the largest city and main economic and cultural center of Mozambique, located on the country’s southern coast along the Indian Ocean.
  • E. 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.
  • 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_69d6aae5ac3c81908d2b0a3a665665b2 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d88dd6913881908becf188c0a7a275 completed April 10, 2026, 5:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69e713d18ccc8190a63256c3cc1c2f59 completed April 21, 2026, 6:06 a.m.
Created at: April 8, 2026, 9:38 p.m.