Triple

T21588098
Position Surface form Disambiguated ID Type / Status
Subject Umbundu language E532704 entity
Predicate ethnicPopulation P2750 FINISHED
Object Ovimbundu 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: Ovimbundu | Statement: [Umbundu language, ethnicPopulation, Ovimbundu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ovimbundu
Context triple: [Umbundu language, ethnicPopulation, Ovimbundu]
  • A. Mbundu
    Mbundu is a major Bantu ethnic group of Angola, known for its distinct language and significant cultural and historical influence in the region.
  • B. Mbanderu
    Mbanderu is a subgroup of the Herero people with its own distinct dialect and cultural traditions, primarily found in Namibia and Botswana.
  • C. Umbundu chosen
    Umbundu is a major Bantu language spoken primarily in central and southern Angola, especially by the Ovimbundu people.
  • D. Lubemba
    Lubemba is the traditional kingdom and cultural heartland of the Bemba people in what is now northern Zambia.
  • E. Basoga
    The Basoga are a Bantu-speaking ethnic group predominantly inhabiting Uganda’s Busoga region, known for their rich cultural traditions and use of the Lusoga language.
  • 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_69e0c46251648190876f0427cf2d321b completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69eeeb621ab88190a33a943424ffb306 completed April 27, 2026, 4:51 a.m.
Created at: April 16, 2026, 6:31 p.m.