Triple

T21588104
Position Surface form Disambiguated ID Type / Status
Subject Umbundu language E532704 entity
Predicate closelyRelatedTo P37 FINISHED
Object Kimbundu language 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: Kimbundu language | Statement: [Umbundu language, closelyRelatedTo, Kimbundu language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kimbundu language
Context triple: [Umbundu language, closelyRelatedTo, Kimbundu language]
  • A. Kimbundu chosen
    Kimbundu is a major Bantu language spoken primarily in northwestern Angola, especially around the capital Luanda, by the Ambundu people.
  • B. Konongo language
    The Konongo language is a Bantu language of East Africa, closely related to Sukuma and spoken by the Konongo people.
  • C. 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.
  • D. Mbunda language
    The Mbunda language is a Bantu language spoken primarily by the Mbunda people in parts of Angola and Zambia.
  • E. 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.
  • 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_69e0c46251648190876f0427cf2d321b completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69eeeb621ab88190a33a943424ffb306 completed April 27, 2026, 4:51 a.m.
Created at: April 16, 2026, 6:31 p.m.