Triple

T6548365
Position Surface form Disambiguated ID Type / Status
Subject Aluku language E151066 entity
Predicate hasSubstrateLanguage P11299 FINISHED
Object Kikongo E57354 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: Kikongo | Statement: [Aluku language, hasSubstrateLanguage, Kikongo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kikongo
Context triple: [Aluku language, hasSubstrateLanguage, Kikongo]
  • A. Kikongo chosen
    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.
  • B. Lingala
    Lingala is a Bantu language widely spoken as a lingua franca in the Democratic Republic of the Congo and the Republic of the Congo, especially in urban centers and along the Congo River.
  • C. Kwanyama
    Kwanyama is a major standardized dialect of the Ovambo language spoken primarily in northern Namibia and southern Angola.
  • D. Kimbundu
    Kimbundu is a major Bantu language spoken primarily in northwestern Angola, especially around the capital Luanda, by the Ambundu people.
  • E. 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.
  • 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_69c687f3fd60819083bfa583e5bcfa71 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6adf132a88190af4553857a474ebd completed March 27, 2026, 4:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6d54e11fc81909aa135d7c0f2c193 completed March 27, 2026, 7:06 p.m.
Created at: March 27, 2026, 1:51 p.m.