Triple

T9960871
Position Surface form Disambiguated ID Type / Status
Subject Mount Heha E195562 entity
Predicate nearbyCity P350 FINISHED
Object Bujumbura E673266 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: Bujumbura | Statement: [Mount Heha, nearbyCity, Bujumbura]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bujumbura
Context triple: [Mount Heha, nearbyCity, Bujumbura]
  • A. Bujumbura chosen
    Bujumbura is the largest city and former capital of Burundi, located on the northeastern shore of Lake Tanganyika.
  • B. 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.
  • C. 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.
  • D. Kigali
    Kigali is the capital and largest city of Rwanda, known as a major political and economic hub in East Africa.
  • E. Butare
    Butare is a city in southern Rwanda that became a significant site of massacres and atrocities during the 1994 Rwandan genocide.
  • 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_69ca82eaaa008190a54fa1a9f954b9ad completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb6d219c48190b2084b0eb07ae125 completed April 2, 2026, 12:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2b5d295908190a064fb72d65b6e24 completed April 5, 2026, 7:19 p.m.
Created at: March 30, 2026, 8:47 p.m.