Triple

T16039662
Position Surface form Disambiguated ID Type / Status
Subject Kaonde people E389060 entity
Predicate speak P741 FINISHED
Object Kaonde language E962196 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: Kaonde language | Statement: [Kaonde people, speak, Kaonde language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kaonde language
Context triple: [Kaonde people, speak, Kaonde language]
  • A. Kaonde language chosen
    The Kaonde language is a Bantu language spoken primarily by the Kaonde people of northwestern Zambia and parts of the Democratic Republic of the Congo.
  • B. Konongo language
    The Konongo language is a Bantu language of East Africa, closely related to Sukuma and spoken by the Konongo people.
  • C. Azande language
    Azande language is a Ubangian language spoken primarily by the Azande people across parts of South Sudan, the Central African Republic, and the Democratic Republic of the Congo.
  • D. Nsenga language
    The Nsenga language is a Bantu language spoken primarily in Zambia and neighboring regions, closely related to other languages of the area such as Tumbuka and Chewa.
  • E. Tembe language
    The Tembe language is an indigenous Tupi-Guarani language spoken by the Tembé people of northern Brazil.
  • 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_69d86dada3808190825d5f80d72fbe88 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1833f84188190baa3a452df880284 completed April 17, 2026, 12:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffdbd77c5481908644742a8a8f3e68 completed May 10, 2026, 1:13 a.m.
Created at: April 10, 2026, 4:56 a.m.