Triple

T16702888
Position Surface form Disambiguated ID Type / Status
Subject Common Voice dataset E405893 entity
Predicate hasLanguage P15 FINISHED
Object Kinyarwanda E65621 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: Kinyarwanda | Statement: [Common Voice dataset, hasLanguage, Kinyarwanda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kinyarwanda
Context triple: [Common Voice dataset, hasLanguage, Kinyarwanda]
  • A. Kinyarwanda chosen
    Kinyarwanda is a Bantu language spoken primarily in Rwanda, where it serves as a national and widely used lingua franca.
  • B. Kirundi
    Kirundi is a Bantu language primarily spoken in Burundi and neighboring regions of East Africa.
  • C. 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.
  • D. 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.
  • 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_69d8838db21081909589220fd71440a4 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e38333a6908190a17d2dee2ca622d6 completed April 18, 2026, 1:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a009d38a1348190bf51af9847a16aa5 completed May 10, 2026, 2:59 p.m.
Created at: April 10, 2026, 5:19 a.m.