Triple

T15797815
Position Surface form Disambiguated ID Type / Status
Subject Takic E383026 entity
Predicate hasMember P10 FINISHED
Object Cupeno language E278636 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: Cupeno language | Statement: [Takic, hasMember, Cupeno language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cupeno language
Context triple: [Takic, hasMember, Cupeno language]
  • A. Cupeno language chosen
    The Cupeño language is an endangered Uto-Aztecan language historically spoken by the Cupeño people of Southern California.
  • B. Capul language
    Capul language, also known as Inabaknon, is an Austronesian language spoken primarily on Capul Island in Northern Samar, Philippines.
  • C. Curripaco language
    The Curripaco language is an Arawakan language spoken by the Curripaco people of the Northwest Amazon region in Brazil, Colombia, and Venezuela.
  • D. Cavineña language
    The Cavineña language is an indigenous Tacanan language spoken by the Cavineña people of northern Bolivia.
  • E. Kupa language
    The Kupa language is a Nupoid language spoken by the Kupa people of central Nigeria.
  • 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_69d86da16e188190b89af699f1ed0bfe completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e0b4def80481908f72733ce9133bc6 completed April 16, 2026, 10:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff90b08ab48190892c700f5eb261d8 completed May 9, 2026, 7:53 p.m.
Created at: April 10, 2026, 4:48 a.m.