Triple

T14558296
Position Surface form Disambiguated ID Type / Status
Subject Aku Uka E341599 entity
Predicate titleLanguage P15 FINISHED
Object Jukun language E335163 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: Jukun language | Statement: [Aku Uka, titleLanguage, Jukun language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jukun language
Context triple: [Aku Uka, titleLanguage, Jukun language]
  • A. Jukun language chosen
    The Jukun language is a Niger-Congo language spoken primarily by the Jukun people of central Nigeria, especially in Taraba and surrounding states.
  • B. Teke-Kukuya language
    The Teke-Kukuya language is a Bantu language spoken by the Teke-Kukuya people in the Republic of the Congo and neighboring regions of Central Africa.
  • C. Kisukuma language
    Kisukuma is a major Bantu language spoken primarily by the Sukuma people in northwestern Tanzania.
  • D. Munji language
    The Munji language is an Eastern Iranian language spoken by the Munji people in Afghanistan’s remote Munjan Valley, closely related to the Yidgha language of Pakistan.
  • E. Kiga language
    The Kiga language is a Bantu language spoken primarily by the Bakiga people of southwestern Uganda.
  • 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_69d822db9c8481908213ceb39585f792 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb3881b788190922932fb8ff81160 completed April 14, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69fda9124af481908f43e3b541568e26 completed May 8, 2026, 9:12 a.m.
Created at: April 10, 2026, 1:23 a.m.