Triple

T17200289
Position Surface form Disambiguated ID Type / Status
Subject Government of Burundi E417456 entity
Predicate capital P234 FINISHED
Object Gitega E195559 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: Gitega | Statement: [Government of Burundi, capital, Gitega]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gitega
Context triple: [Government of Burundi, capital, Gitega]
  • A. Gitega chosen
    Gitega is the political and administrative capital city of Burundi, located in the central part of the country.
  • B. Gisenyi
    Gisenyi is a city in northwestern Rwanda on the shores of Lake Kivu, historically significant as one of the key sites affected during the 1994 Rwandan genocide.
  • C. 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.
  • D. Bujumbura
    Bujumbura is the largest city and former capital of Burundi, located on the northeastern shore of Lake Tanganyika.
  • E. Gitega Sector
    Gitega Sector is an administrative subdivision located within Nyarugenge 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_69d886d6ba8c819093215917b3d01689 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42daf2e5c81909c97d2e7a3ed7b88 completed April 19, 2026, 1:19 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0170e784bc8190a052c4fe87be124a completed May 11, 2026, 6:02 a.m.
Created at: April 10, 2026, 5:38 a.m.