Triple

T14010540
Position Surface form Disambiguated ID Type / Status
Subject Nupoid E337065 entity
Predicate hasMember P10 FINISHED
Object Kupa language E1073883 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: Kupa language | Statement: [Nupoid, hasMember, Kupa language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kupa language
Context triple: [Nupoid, hasMember, Kupa language]
  • A. Kupa language chosen
    The Kupa language is a Nupoid language spoken by the Kupa people of central Nigeria.
  • B. Cupeno language
    The Cupeño language is an endangered Uto-Aztecan language historically spoken by the Cupeño people of Southern California.
  • C. Capul language
    Capul language, also known as Inabaknon, is an Austronesian language spoken primarily on Capul Island in Northern Samar, Philippines.
  • D. Khaput language
    The Khaput language is a lesser-known member of the Northeast Caucasian language family spoken by a small community in the Caucasus region.
  • E. Kapon languages
    Kapon languages are a small group of closely related Cariban languages spoken by indigenous Kapon peoples in the Guiana Highlands of northern South America.
  • 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_69d81c645c5c8190b1fd16a285a1b78a completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2ed5cfd0819085b9c860b119a9de completed April 14, 2026, 12:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69fbc32b459c81908b652286f444e940 completed May 6, 2026, 10:39 p.m.
Created at: April 9, 2026, 10:19 p.m.