Triple

T19145330
Position Surface form Disambiguated ID Type / Status
Subject Gbaya E468663 entity
Predicate language P15 FINISHED
Object Bokoto 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: Bokoto language | Statement: [Gbaya, language, Bokoto language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bokoto language
Context triple: [Gbaya, language, Bokoto language]
  • A. Bokoto language chosen
    The Bokoto language is a Gbaya language spoken by the Bokoto people of Central Africa, primarily in the Central African Republic and surrounding regions.
  • B. Bafut language
    The Bafut language is a Grassfields Bantu language spoken primarily by the Bafut people in the Northwest Region of Cameroon.
  • C. 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.
  • D. Babanki language
    The Babanki language is a Grassfields Bantu language spoken by the Babanki people in Cameroon.
  • E. Sanglechi language
    The Sanglechi language is an Eastern Iranian language spoken by a small community in the Sanglech Valley region of Afghanistan and Tajikistan.
  • 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_69d8dd084ff48190ac0f8c46ee722629 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5e978b0b481909a531efa030c5def completed April 20, 2026, 8:53 a.m.
Created at: April 10, 2026, 12:06 p.m.