Triple

T10489341
Position Surface form Disambiguated ID Type / Status
Subject Maba language E247372 entity
Predicate hasAlternativeName P39 FINISHED
Object Bura Mabang E402509 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: Bura Mabang | Statement: [Maba language, hasAlternativeName, Bura Mabang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bura Mabang
Context triple: [Maba language, hasAlternativeName, Bura Mabang]
  • A. Bura
    Bura is a strong, cold, and dry northeasterly wind that blows from the interior toward the Adriatic Sea, particularly affecting coastal regions of Croatia and neighboring areas.
  • B. Bura chosen
    Bura is a Central Chadic language spoken primarily in northeastern Nigeria, known for its complex tonal system and rich verbal morphology.
  • C. Matabaan
    Matabaan is a town in central Somalia that serves as one of the urban centers within the federal member state of Hirshabelle.
  • D. Ngamo
    Ngamo is a West Chadic language spoken primarily in northeastern Nigeria by the Ngamo people.
  • E. Buhera
    Buhera is a rural town and district center in eastern Zimbabwe known for its agricultural activities and location within Manicaland Province.
  • 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_69d381c309b88190af78aa681cf6a4c2 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d5097ca5c081908b47a08ca7885650 completed April 7, 2026, 1:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69d8dc9792308190b09d6aaed63dd418 completed April 10, 2026, 11:18 a.m.
Created at: April 6, 2026, 12:23 p.m.