Triple

T14661178
Position Surface form Disambiguated ID Type / Status
Subject Guna of Madungandí E344240 entity
Predicate hasAncestor P369 FINISHED
Object Guna language E68751 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: Guna language | Statement: [Guna of Madungandí, hasAncestor, Guna language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guna language
Context triple: [Guna of Madungandí, hasAncestor, Guna language]
  • A. Guna language chosen
    Guna language is an indigenous Chibchan language spoken by the Guna people of Panama and Colombia.
  • B. Ganguela language
    The Ganguela language is a Bantu language spoken by the Ganguela people of southwestern Africa, particularly in Angola.
  • C. Gura language
    The Gura language is an Ethiopian Semitic language spoken by the Gurage people in central Ethiopia.
  • D. Gudu language
    The Gudu language is a lesser-known Bantoid (Bena–Mboi) language spoken by a small ethnic community in northeastern Nigeria.
  • E. Gonja language
    The Gonja language is a Gur language spoken primarily by the Gonja people in northern Ghana.
  • 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_69d822e283fc8190a0e4c235cf880052 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb51c84448190a1f5fa9ab8a1e2c4 completed April 14, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdfb7c7df88190a4e551a12f6e8158 completed May 8, 2026, 3:04 p.m.
Created at: April 10, 2026, 1:27 a.m.