Triple

T11921583
Position Surface form Disambiguated ID Type / Status
Subject Kayunga District E283668 entity
Predicate ethnicGroup P194 FINISHED
Object Baganda E275004 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: Baganda | Statement: [Kayunga District, ethnicGroup, Baganda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Baganda
Context triple: [Kayunga District, ethnicGroup, Baganda]
  • A. Baganda chosen
    The Baganda are the largest ethnic group in Uganda, historically centered in the Buganda Kingdom and known for their rich cultural traditions and Luganda language.
  • 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. Kitwe
    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.
  • 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. Tumbuka
    Tumbuka is a Bantu language spoken primarily in northern Malawi and parts of Zambia and Tanzania.
  • 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_69d6ab2ce9c48190b5d39511b524f666 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8e8e1b08481909ed291667035f330 completed April 10, 2026, 12:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69f44033c288819099587af3f895eac5 completed May 1, 2026, 5:54 a.m.
Created at: April 8, 2026, 9:45 p.m.