Triple

T17646161
Position Surface form Disambiguated ID Type / Status
Subject Herero language E429363 entity
Predicate closelyRelatedTo P37 FINISHED
Object Ovambo language NE NERFINISHED

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: Ovambo language | Statement: [Herero language, closelyRelatedTo, Ovambo language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ovambo language
Context triple: [Herero language, closelyRelatedTo, Ovambo language]
  • A. Ovambo language chosen
    The Ovambo language is a Bantu language spoken primarily in northern Namibia and southern Angola by the Ovambo people.
  • B. Ngamo language
    The Ngamo language is a West Chadic language spoken primarily in northeastern Nigeria by the Ngamo people.
  • C. Haiǁom language
    The Haiǁom language is a Khoisan language spoken by the Haiǁom people of Namibia, known for its use of click consonants and close relation to Nama.
  • D. Teke-Ngungwel language
    The Teke-Ngungwel language is a Bantu language spoken by the Teke people in Central Africa, particularly in parts of the Republic of the Congo and neighboring regions.
  • E. Marakwet language
    The Marakwet language is a Southern Nilotic language spoken by the Marakwet people of Kenya and is closely related to other Kalenjin languages such as Kipsigis.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889e2c2608190b762e76d9b2262f1 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e46e39937881909bb6a1792fff39a9 completed April 19, 2026, 5:55 a.m.
Created at: April 10, 2026, 6:04 a.m.