Triple

T18409186
Position Surface form Disambiguated ID Type / Status
Subject Ochiherero E441706 entity
Predicate hasDialect P4251 FINISHED
Object Mbanderu 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: Mbanderu | Statement: [Ochiherero, hasDialect, Mbanderu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mbanderu
Context triple: [Ochiherero, hasDialect, Mbanderu]
  • A. Mbanderu chosen
    Mbanderu is a subgroup of the Herero people with its own distinct dialect and cultural traditions, primarily found in Namibia and Botswana.
  • B. Ngbandi
    Ngbandi is a Central African language spoken primarily in the Democratic Republic of the Congo and the Central African Republic, known for its role as a regional lingua franca and its inclusion in the Ubangian language family.
  • C. Lubemba
    Lubemba is the traditional kingdom and cultural heartland of the Bemba people in what is now northern Zambia.
  • D. Umbundu
    Umbundu is a major Bantu language spoken primarily in central and southern Angola, especially by the Ovimbundu people.
  • E. Mutombo
    Mutombo is a retired Congolese-American NBA Hall of Fame center renowned for his dominant shot-blocking, defensive prowess, and humanitarian work.
  • 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_69d8b9eb8a508190a942fd75ebd8b1dc completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e5195b98808190b9cfb2e444f2b524 completed April 19, 2026, 6:05 p.m.
Created at: April 10, 2026, 10:47 a.m.