Triple

T11575123
Position Surface form Disambiguated ID Type / Status
Subject Sango language E274482 entity
Predicate hasLexicalSource P9129 FINISHED
Object Ngbandi E672799 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 | Statement: [Sango language, hasLexicalSource, Ngbandi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ngbandi
Context triple: [Sango language, hasLexicalSource, Ngbandi]
  • A. Ngbandi chosen
    Ngbandi is a Central African language spoken primarily in the Democratic Republic of the Congo and the Central African Republic, known for its role as a regional lingua franca and its inclusion in the Ubangian language family.
  • B. Mbanderu
    Mbanderu is a subgroup of the Herero people with its own distinct dialect and cultural traditions, primarily found in Namibia and Botswana.
  • C. Banda-Yangere
    Banda-Yangere is a dialect of the Central Banda language spoken by Banda communities in parts of Central Africa.
  • D. Makouda
    Makouda is a town and commune located in northern Algeria within the Kabylie region.
  • E. N’Guigmi
    N’Guigmi is a town and commune in southeastern Niger, located near Lake Chad and serving as an important local center for trade and transport.
  • 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_69d89048120c81908258f984711f7dd4 completed April 10, 2026, 5:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69e713e49f508190b9bad316d68eab42 completed April 21, 2026, 6:06 a.m.
Created at: April 8, 2026, 9:38 p.m.