Triple

T11578481
Position Surface form Disambiguated ID Type / Status
Subject Sango E274564 entity
Predicate basedOn P98 FINISHED
Object Ngbandi language E274483 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: Ngbandi language | Statement: [Sango, basedOn, Ngbandi language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ngbandi language
Context triple: [Sango, basedOn, Ngbandi language]
  • A. Ngbandi language chosen
    The Ngbandi language is a Central Sudanic language spoken primarily in the Central African Republic and the Democratic Republic of the Congo, known for being the linguistic source of the trade language Sango.
  • B. Banda-Ndélé language
    The Banda-Ndélé language is a Central Sudanic language spoken by the Banda people, primarily in the Central African Republic.
  • C. Banda-Gbi language
    The Banda-Gbi language is a Central Sudanic language spoken by the Banda people of the Central African Republic and surrounding regions.
  • D. Banda-Mbrém language
    The Banda-Mbrém language is a Central Sudanic language spoken by the Banda people in parts of Central Africa, particularly in the Central African Republic.
  • E. Bafut language
    The Bafut language is a Grassfields Bantu language spoken primarily by the Bafut people in the Northwest Region of Cameroon.
  • 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_69d6aae5ac3c81908d2b0a3a665665b2 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8904b46288190890ecafd6ceb0c3d completed April 10, 2026, 5:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef8269c4f48190aaf238a64c5caf1d completed April 27, 2026, 3:36 p.m.
Created at: April 8, 2026, 9:38 p.m.