Triple

T21917135
Position Surface form Disambiguated ID Type / Status
Subject Bamileke languages E541208 entity
Predicate hasMember P10 FINISHED
Object Medumba 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: Medumba language | Statement: [Bamileke languages, hasMember, Medumba language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Medumba language
Context triple: [Bamileke languages, hasMember, Medumba language]
  • A. Medumba language chosen
    Medumba is a Bantu-related Grassfields language spoken primarily by the Bamileke people in western Cameroon.
  • B. Kumbewaha language
    The Kumbewaha language is an Austronesian language spoken in Sulawesi, Indonesia, belonging to the Wotu–Wolio subgroup.
  • C. Mambae language
    The Mambae language is an Austronesian language spoken primarily in East Timor, notable for its role in local identity and traditional culture.
  • D. Chumburung language
    The Chumburung language is a Niger-Congo language spoken primarily by the Chumburung people in Ghana.
  • E. Tembe language
    The Tembe language is an indigenous Tupi-Guarani language spoken by the Tembé people of northern Brazil.
  • 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_69e0c47c4b9c8190a5586a75f5f36453 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f1233858308190a877d8015db4d380 completed April 28, 2026, 9:14 p.m.
Created at: April 16, 2026, 7:43 p.m.