Triple

T16368452
Position Surface form Disambiguated ID Type / Status
Subject Wilbur Smith E397497 entity
Predicate placeOfBirth P1 FINISHED
Object Kabwe E397497 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: Kabwe | Statement: [Wilbur Smith, placeOfBirth, Kabwe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kabwe
Context triple: [Wilbur Smith, placeOfBirth, Kabwe]
  • A. Kabwe, Zambia chosen
    Kabwe, Zambia is a central Zambian town historically known as a major mining and railway hub and as the birthplace of novelist Wilbur Smith.
  • B. Goma
    Goma is a city in eastern Democratic Republic of the Congo on the northern shore of Lake Kivu, known as a gateway to Virunga National Park and for its proximity to the active Nyiragongo volcano.
  • C. Malaba
    Malaba is a key border town between Uganda and Kenya that serves as a major transit point for regional trade and transport.
  • D. Kalulushi
    Kalulushi is a town in Zambia known for its copper mining activities and location within the country's industrial Copperbelt region.
  • E. Kabwe District
    Kabwe District is an administrative region in Zambia’s Central Province that encompasses the city of Kabwe and its surrounding areas.
  • 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_69d87f2778dc8190aa95c7572db127e6 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2ff3f0694819097faa1c1447a9e97 completed April 18, 2026, 3:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0035600420819087c909a615d205a2 completed May 10, 2026, 7:36 a.m.
Created at: April 10, 2026, 5:08 a.m.