Triple

T741142
Position Surface form Disambiguated ID Type / Status
Subject ECA Subregional Office for Eastern Africa E15245 entity
Predicate locatedIn P40 FINISHED
Object Kigali E87281 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 | Statement: [ECA Subregional Office for Eastern Africa, locatedIn, Kigali]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kigali
Context triple: [ECA Subregional Office for Eastern Africa, locatedIn, Kigali]
  • A. Kigali chosen
    Kigali is the capital and largest city of Rwanda, known as a major political and economic hub in East Africa.
  • B. Masvingo
    Masvingo is one of Zimbabwe’s oldest urban centers, located in the country’s southeastern region near the Great Zimbabwe ruins.
  • C. Africa/Bujumbura
    Africa/Bujumbura is the IANA time zone identifier representing the local time observed in Bujumbura, Burundi, which follows Central Africa Time.
  • D. Butaro, Rwanda
    Butaro, Rwanda is a rural town in northern Rwanda known for its innovative, community-focused health facilities and scenic volcanic landscapes.
  • E. Kampala
    Kampala is the capital and largest city of Uganda, serving as the country’s political, economic, and cultural center.
  • 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_69a49358aa308190adbc9b5a0a2adcf9 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a5f4ccb48190a4eb8679a59d8e24 completed March 1, 2026, 8:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69a654e40b9c8190ab4314e63826d00a completed March 3, 2026, 3:26 a.m.
Created at: March 1, 2026, 7:37 p.m.