Triple

T16428005
Position Surface form Disambiguated ID Type / Status
Subject Kicukiro District E398994 entity
Predicate hasUrbanArea P316 FINISHED
Object Kigarama sector E1213311 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: Kigarama sector | Statement: [Kicukiro District, hasUrbanArea, Kigarama sector]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kigarama sector
Context triple: [Kicukiro District, hasUrbanArea, Kigarama sector]
  • A. Kagarama sector chosen
    Kagarama sector is an urban administrative area within Kigali, Rwanda, known for hosting key district offices and residential neighborhoods in Kicukiro District.
  • B. Rusororo sector
    Rusororo sector is an administrative sector within Gasabo District in Kigali, Rwanda, known for its rapidly growing residential areas and proximity to key urban infrastructure.
  • C. Kicukiro sector
    Kicukiro sector is an urban administrative sector within Kigali, Rwanda, known for its residential neighborhoods, commercial activity, and proximity to key city infrastructure.
  • D. Rutunga sector
    Rutunga sector is an administrative sector located within Gasabo District in Kigali, Rwanda.
  • E. Niboye sector
    Niboye sector is an urban administrative sector within Kicukiro District in Kigali, Rwanda.
  • 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_69d87f2b9024819085c20e52de95d583 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e328fc223c8190bbed29907351a6f6 completed April 18, 2026, 6:47 a.m.
NED1 Entity disambiguation (via context triple) batch_6a004f477674819093bcf9f0df43ebf9 completed May 10, 2026, 9:26 a.m.
Created at: April 10, 2026, 5:09 a.m.