Triple

T16751700
Position Surface form Disambiguated ID Type / Status
Subject Southern Cameroon E407096 entity
Predicate hasLanguage P15 FINISHED
Object Ewondo language E91177 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: Ewondo language | Statement: [Southern Cameroon, hasLanguage, Ewondo language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ewondo language
Context triple: [Southern Cameroon, hasLanguage, Ewondo language]
  • A. Ewondo language chosen
    Ewondo is a Bantu language spoken primarily in central Cameroon, notably around the capital Yaoundé, by the Ewondo (Yaoundé) people.
  • B. Bulu-Ewondo languages
    The Bulu-Ewondo languages are a subgroup of Bantu languages spoken primarily in Cameroon, closely associated with the Beti-Fang linguistic and cultural area.
  • C. Sateré-Mawé language
    The Sateré-Mawé language is an indigenous Tupian language spoken by the Sateré-Mawé people of the Brazilian Amazon.
  • D. Effutu language
    Effutu language is a Niger-Congo language spoken primarily by the Effutu people in and around the coastal town of Winneba in Ghana.
  • E. Tontemboan language
    The Tontemboan language is an Austronesian language spoken by the Tontemboan people of North Sulawesi, Indonesia, and is one of the traditional Minahasan languages of the 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_69d8838ffb088190a0b11149929006bf completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3aa271de48190b4a535408aeef734 completed April 18, 2026, 3:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00a52402848190b029cb0be31b4c74 completed May 10, 2026, 3:32 p.m.
Created at: April 10, 2026, 5:21 a.m.