Triple

T16506121
Position Surface form Disambiguated ID Type / Status
Subject Nyarugenge District E400935 entity
Predicate contains P35 FINISHED
Object Kigali Sector E1236565 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: Kigali Sector | Statement: [Nyarugenge District, contains, Kigali Sector]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kigali Sector
Context triple: [Nyarugenge District, contains, Kigali Sector]
  • A. Kigali sector chosen
    Kigali sector is an administrative subdivision within Rwanda’s capital area, forming part of the urban governance structure of Gasabo District in Kigali City.
  • B. Kigali Central Business District
    Kigali Central Business District is the main commercial and financial hub of Kigali, featuring high-rise offices, major businesses, and key government institutions.
  • C. Kigali Province
    Kigali Province is an administrative region in central Rwanda that encompasses the nation’s capital city, Kigali, and serves as its political and economic hub.
  • D. Gitega Sector
    Gitega Sector is an administrative subdivision located within Nyarugenge District in Kigali, Rwanda.
  • E. Kigali Special Economic Zone
    Kigali Special Economic Zone is a major industrial and business hub in Kigali, Rwanda, designed to attract investment, promote manufacturing, and support export-oriented economic growth.
  • 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_69d88381f6148190819958a038be990e completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e32e52a2b48190ae715e7db0fd3aad completed April 18, 2026, 7:10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01673979608190905afae3071413c0 completed May 11, 2026, 5:20 a.m.
Created at: April 10, 2026, 5:14 a.m.