Triple

T7952589
Position Surface form Disambiguated ID Type / Status
Subject Bemba people E184650 entity
Predicate significantUrbanPresence P40494 FINISHED
Object Lusaka E31817 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: Lusaka | Statement: [Bemba people, significantUrbanPresence, Lusaka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lusaka
Context triple: [Bemba people, significantUrbanPresence, Lusaka]
  • A. Lusaka, Zambia chosen
    Lusaka, Zambia is the capital and largest city of Zambia, serving as the country’s political, economic, and cultural center.
  • B. Lilongwe
    Lilongwe is the largest city and administrative and political center of Malawi, located in the country’s central region.
  • C. Matadi
    Matadi is a major port city in western Democratic Republic of the Congo, serving as the country’s principal seaport and a key gateway for trade between the Atlantic Ocean and the interior via the Congo River.
  • D. Lubumbashi
    Lubumbashi is the second-largest city in the Democratic Republic of the Congo and a major mining and commercial center in the southeastern part of the country.
  • E. Kasane
    Kasane is a small town in northern Botswana that serves as a key gateway and service hub for visitors to Chobe National Park and the surrounding wildlife 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_69ca8292cba881908a64427b938dac47 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3b5e51c88190abcc0534723e3660 completed March 31, 2026, 3:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd33cf48188190b57ac2fb1dbfa771 completed April 1, 2026, 3:03 p.m.
Created at: March 30, 2026, 5:10 p.m.