Triple

T18074098
Position Surface form Disambiguated ID Type / Status
Subject Lukiiko E432508 entity
Predicate seat P75 FINISHED
Object Bulange 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: Bulange | Statement: [Lukiiko, seat, Bulange]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bulange
Context triple: [Lukiiko, seat, Bulange]
  • A. Bulange chosen
    Bulange is the historic administrative building of the Buganda Kingdom in Kampala, Uganda, serving as the seat of the Lukiiko (parliament) and the Kabaka’s offices.
  • B. Bolongongo
    Bolongongo is a town and municipality located in Angola’s Cuanza Norte Province.
  • C. Gwembe
    Gwembe is a small town in southern Zambia situated near the Zambezi Valley, historically associated with Tonga communities and resettlement related to the Kariba Dam.
  • D. Mberengwa
    Mberengwa is a rural district and growth point in Zimbabwe known for its mining activities and location in the southern part of the Midlands Province.
  • E. Bongwe
    Bongwe is a dialect of the Duala language spoken by the Duala people of Cameroon.
  • 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_69d8b9070cac81909fa9473fb1c3f1c7 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4ccefcdc4819086d0b224731bfc4d completed April 19, 2026, 12:39 p.m.
Created at: April 10, 2026, 10:26 a.m.