Triple

T17200321
Position Surface form Disambiguated ID Type / Status
Subject Government of Burundi E417456 entity
Predicate officialLanguage P236 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: [Government of Burundi, officialLanguage, Kirundi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kirundi
Context triple: [Government of Burundi, officialLanguage, 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_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_6a015fda06788190882aef1a57356e41 completed May 11, 2026, 4:49 a.m.
Created at: April 10, 2026, 5:38 a.m.