Triple

T13593650
Position Surface form Disambiguated ID Type / Status
Subject Mutare City Hall E324757 entity
Predicate hasLanguageOfAdministration P236 FINISHED
Object Ndau E147443 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: Ndau | Statement: [Mutare City Hall, hasLanguageOfAdministration, Ndau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ndau
Context triple: [Mutare City Hall, hasLanguageOfAdministration, Ndau]
  • A. Ndau chosen
    Ndau is a Southern Bantu language spoken primarily in central Mozambique and eastern Zimbabwe, closely related to Shona.
  • B. Nkoya
    Nkoya is a Bantu language spoken primarily in western Zambia by the Nkoya people.
  • C. Mpongwe
    Mpongwe is a Bantu language variety spoken primarily in Gabon, recognized as one of the main dialects of the Myene language cluster.
  • D. Nyakyusa
    The Nyakyusa are a Bantu-speaking ethnic group primarily inhabiting the northern shores of Lake Malawi in southern Tanzania, known for their intensive agriculture and distinctive age-village social system.
  • E. Inibaloi
    Inibaloi is an Austronesian language spoken by the Ibaloi people of the northern Philippines, particularly in Benguet province on Luzon.
  • 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_69d80769eaf081909d82f44e484d6113 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb057f1c881909a3bb77c659a724a completed April 12, 2026, 2:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f76bc762a08190b5d29cef9923da84 completed May 3, 2026, 3:37 p.m.
Created at: April 9, 2026, 9:49 p.m.