Triple

T22765591
Position Surface form Disambiguated ID Type / Status
Subject Adamawa Region E563113 entity
Predicate hasDepartment P35 FINISHED
Object Mbéré Department 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: Mbéré Department | Statement: [Adamawa Region, hasDepartment, Mbéré Department]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mbéré Department
Context triple: [Adamawa Region, hasDepartment, Mbéré Department]
  • A. Mbéré Department chosen
    Mbéré Department is an administrative division in the Adamawa Region of Cameroon, known for its predominantly rural communities and the town of Meiganga as a key local center.
  • B. Ndé Department
    Ndé Department is an administrative division in western Cameroon known for its predominantly rural communities and agricultural activities.
  • C. Boumba-et-Ngoko Department
    Boumba-et-Ngoko Department is an administrative division in southeastern Cameroon known for its vast rainforest areas, low population density, and rich biodiversity.
  • D. Lopé Department
    Lopé Department is an administrative division in central Gabon known for encompassing parts of the ecologically rich Lopé National Park.
  • E. Ouémé Department
    Ouémé Department is an administrative region in southeastern Benin that includes the national capital, Porto-Novo, and is known for its role as a political and economic hub.
  • 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_69e24552e11c81909c2d61578a558bd7 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17a80249c819091569e7b8d500b45 completed April 29, 2026, 3:26 a.m.
Created at: April 17, 2026, 3:26 p.m.