Triple

T23348700
Position Surface form Disambiguated ID Type / Status
Subject Duala (Cameroon) E591942 entity
Predicate closelyRelatedTo P37 FINISHED
Object Bakweri 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: Bakweri language | Statement: [Duala (Cameroon), closelyRelatedTo, Bakweri language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bakweri language
Context triple: [Duala (Cameroon), closelyRelatedTo, Bakweri language]
  • A. Bakweri language chosen
    The Bakweri language is a Bantu language spoken by the Bakweri people primarily around Mount Cameroon in southwestern Cameroon.
  • B. Bakairi language
    The Bakairi language is an indigenous Cariban language spoken by the Bakairi people of central Brazil, known for its endangered status and significance to the cultural identity of its speakers.
  • C. Bekwarra language
    The Bekwarra language is a Niger-Congo language spoken primarily by the Bekwarra people of Cross River State in southeastern Nigeria.
  • D. Baka language
    The Baka language is a Central African language spoken primarily by the Baka Pygmy communities in parts of Cameroon, Gabon, and the Republic of the Congo.
  • E. Bafia language
    The Bafia language is a Bantu language spoken primarily by the Bafia people in central Cameroon.
  • 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_69e25d20e3d08190bcede87673cafb25 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f199cb2a3c8190a5c0c8d8735256c7 completed April 29, 2026, 5:40 a.m.
Created at: April 17, 2026, 5:19 p.m.