Triple

T12617788
Position Surface form Disambiguated ID Type / Status
Subject Kwinti E301297 entity
Predicate linguisticRelation P10003 FINISHED
Object Ndyuka language E28673 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: Ndyuka language | Statement: [Kwinti, linguisticRelation, Ndyuka language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ndyuka language
Context triple: [Kwinti, linguisticRelation, Ndyuka language]
  • A. Ndyuka language chosen
    The Ndyuka language is an English-based creole spoken primarily by the Ndyuka Maroon community in Suriname and French Guiana.
  • B. Nyishi language
    The Nyishi language is a Tani (Tibeto-Burman) language spoken primarily by the Nyishi people of Arunachal Pradesh in northeastern India.
  • C. Nyindrou language
    The Nyindrou language is an Oceanic language spoken by communities in the Admiralty Islands of Papua New Guinea.
  • D. Buyi language
    The Buyi language is a Tai–Kadai language spoken primarily by the Buyi ethnic group in Guizhou and neighboring regions of southern China.
  • E. Dyula language
    The Dyula language is a Mande language of West Africa widely used as a trade and lingua franca in countries such as Côte d’Ivoire, Burkina Faso, and Mali.
  • 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_69d7bdeaf49c8190b13800111fa77ea3 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d960c63ea48190ae1aae9280a023a6 completed April 10, 2026, 8:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69f65ed507988190b9d46586f3c3584c completed May 2, 2026, 8:30 p.m.
Created at: April 9, 2026, 5:13 p.m.