Triple

T19891589
Position Surface form Disambiguated ID Type / Status
Subject Central Province, Zambia E478043 entity
Predicate hasCity P316 FINISHED
Object Kabwe 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: Kabwe | Statement: [Central Province, Zambia, hasCity, Kabwe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kabwe
Context triple: [Central Province, Zambia, hasCity, 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. Kinshaldy
    Kinshaldy is a coastal area in Fife, Scotland, known for its expansive sandy beach, dunes, and proximity to Tentsmuir Forest.
  • 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_69d8e51f32b08190b3687f4f60353250 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e6590ed7988190bc6b610d1f4fa194 completed April 20, 2026, 4:49 p.m.
Created at: April 10, 2026, 1:52 p.m.