Triple

T11856793
Position Surface form Disambiguated ID Type / Status
Subject West Central Sudanic languages E282059 entity
Predicate hasMember P10 FINISHED
Object Kaba language E262847 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: Kaba language | Statement: [West Central Sudanic languages, hasMember, Kaba language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kaba language
Context triple: [West Central Sudanic languages, hasMember, Kaba language]
  • A. Kaba language chosen
    The Kaba language is a Central Sudanic language spoken primarily in parts of Chad and the Central African Republic by Kaba ethnic groups.
  • B. Kabba language
    Kabba is a Niger-Congo language of the Adamawa–Ubangi branch spoken primarily in the Central African Republic.
  • C. Babanki language
    The Babanki language is a Grassfields Bantu language spoken by the Babanki people in Cameroon.
  • D. Kaxabu language
    The Kaxabu language is an indigenous Formosan language of Taiwan spoken by the Kaxabu people and considered highly endangered.
  • E. Dagbani language
    Dagbani is a major Gur language of northern Ghana, spoken primarily by the Dagomba people and used widely in education, media, and regional communication.
  • 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_69d6ab287ba48190a5178779fd19b9b7 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a699089c8190b7a298baf13dcded completed April 10, 2026, 7:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69f167d9b9e8819093582637941fc5ca completed April 29, 2026, 2:07 a.m.
Created at: April 8, 2026, 9:43 p.m.