Triple

T6040791
Position Surface form Disambiguated ID Type / Status
Subject Parliament of Rwanda E134537 entity
Predicate meetsIn P40 FINISHED
Object City of 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: City of Kigali | Statement: [Parliament of Rwanda, meetsIn, City of Kigali]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Kigali
Context triple: [Parliament of Rwanda, meetsIn, City of 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. Gitega
    Gitega is the political and administrative capital city of Burundi, located in the central part of the country.
  • C. Butaro, Rwanda
    Butaro, Rwanda is a rural town in northern Rwanda known for its innovative, community-focused health facilities and scenic volcanic landscapes.
  • D. 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.
  • E. Bukavu
    Bukavu is a major city in the eastern Democratic Republic of the Congo, located on the southwestern shore of Lake Kivu near the Rwandan border.
  • 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_69c00875db5c819099dd5bb833ec43c2 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c056cf82d481909d5161fe3643e7ed completed March 22, 2026, 8:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69c11cfbb4cc81909736d5d041dd0b23 completed March 23, 2026, 10:59 a.m.
Created at: March 22, 2026, 4:08 p.m.