Triple

T6701050
Position Surface form Disambiguated ID Type / Status
Subject Proto-Bantu E152878 entity
Predicate ancestorOf P369 FINISHED
Object Luba-Katanga language E300902 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: Luba-Katanga language | Statement: [Proto-Bantu, ancestorOf, Luba-Katanga language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Luba-Katanga language
Context triple: [Proto-Bantu, ancestorOf, Luba-Katanga language]
  • A. Luba languages chosen
    The Luba languages are a group of closely related Bantu languages spoken primarily in the Democratic Republic of the Congo by the Luba people and neighboring communities.
  • B. Kikongo
    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.
  • C. 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.
  • D. Bemba language
    Bemba is a major Bantu language spoken primarily in Zambia, serving as one of the country’s most widely used lingua francas in daily life, education, and media.
  • E. Tumbuka
    Tumbuka is a Bantu language spoken primarily in northern Malawi and parts of Zambia and Tanzania.
  • 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_69c68807adbc8190b8632df42b39eda0 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d0e4a1848190997520ddd7808cc6 completed March 27, 2026, 6:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7129315c08190a9b72b8119c71e20 completed March 27, 2026, 11:28 p.m.
Created at: March 27, 2026, 2:05 p.m.