Triple

T16553215
Position Surface form Disambiguated ID Type / Status
Subject Nama people E402124 entity
Predicate language P15 FINISHED
Object Nama language E414989 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: Nama language | Statement: [Nama people, language, Nama language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nama language
Context triple: [Nama people, language, Nama language]
  • A. Nama language chosen
    Nama language is a Khoe (Khoisan) language of southern Africa, primarily spoken by the Nama people in Namibia and neighboring regions.
  • B. Nume language
    Nume language is an Oceanic language spoken by a small community on the island of Gaua in the Banks Islands of northern Vanuatu.
  • C. Nambya language
    Nambya is a Bantu language spoken primarily in northwestern Zimbabwe and northeastern Botswana, closely related to Kalanga and used by the Nambya people.
  • D. Nafe (Nguna) language
    The Nafe (Nguna) language is an Oceanic Austronesian language spoken on Nguna Island and nearby areas in central Vanuatu.
  • E. Nembe language
    The Nembe language is an Ijoid language spoken primarily by the Nembe people in Bayelsa State in Nigeria’s Niger Delta region.
  • 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_69d88384bc30819084229e7dcdc39a41 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e34fc737ac8190b755e2a39b6ef32b completed April 18, 2026, 9:32 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0067b87b608190950b8f14e6aceed3 completed May 10, 2026, 11:10 a.m.
Created at: April 10, 2026, 5:15 a.m.