Triple

T14625072
Position Surface form Disambiguated ID Type / Status
Subject Mufulira E343322 entity
Predicate hasNearbyCity P350 FINISHED
Object Kitwe E343321 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: Kitwe | Statement: [Mufulira, hasNearbyCity, Kitwe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kitwe
Context triple: [Mufulira, hasNearbyCity, Kitwe]
  • A. Kitwe chosen
    Kitwe is a major mining and industrial city in Zambia’s Copperbelt Province, known as one of the country’s largest urban and economic centers.
  • B. Luganda
    Luganda is a major Bantu language spoken primarily in Uganda, serving as a key lingua franca and cultural language of the Baganda people.
  • C. Kirundi
    Kirundi is a Bantu language primarily spoken in Burundi and neighboring regions of East Africa.
  • D. Kikongo
    Kikongo is a Bantu language widely spoken in Central Africa, particularly in the western regions of the Democratic Republic of the Congo and neighboring countries.
  • E. Kinyarwanda
    Kinyarwanda is a Bantu language spoken primarily in Rwanda, where it serves as a national and widely used lingua franca.
  • 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_69d822dffc3c8190aa173b90761bffda completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb46a4a9081908472b0a542028a7f completed April 14, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fda92a6b9c8190bdb220444cfbe34a completed May 8, 2026, 9:13 a.m.
Created at: April 10, 2026, 1:26 a.m.