Triple

T12809606
Position Surface form Disambiguated ID Type / Status
Subject Burundian Civil War E306234 entity
Predicate language P15 FINISHED
Object Kirundi E43853 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: Kirundi | Statement: [Burundian Civil War, language, Kirundi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kirundi
Context triple: [Burundian Civil War, language, Kirundi]
  • A. Kirundi chosen
    Kirundi is a Bantu language primarily spoken in Burundi and neighboring regions of East Africa.
  • B. Kinyarwanda
    Kinyarwanda is a Bantu language spoken primarily in Rwanda, where it serves as a national and widely used lingua franca.
  • C. Kitwe
    Kitwe is a major mining and industrial city in Zambia’s Copperbelt Province, known as one of the country’s largest urban and economic centers.
  • D. Kinyarwanda–Rundi languages
    The Kinyarwanda–Rundi languages are a closely related cluster of Bantu languages spoken primarily in Rwanda and Burundi, including Kinyarwanda and Kirundi.
  • E. Kikongo
    Kikongo is a Bantu language widely spoken in Central Africa, particularly in the western regions of the Democratic Republic of the Congo and neighboring countries.
  • 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_69d7bdf46c448190b1faa55aaacb6317 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96e817598819080fdd61e9d61236e completed April 10, 2026, 9:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69f68ec89eb081909915af6e2216e0a2 completed May 2, 2026, 11:54 p.m.
Created at: April 9, 2026, 5:31 p.m.