Triple

T18344991
Position Surface form Disambiguated ID Type / Status
Subject ISO 3166-2:ST E439512 entity
Predicate definesSubdivision P747 FINISHED
Object Príncipe 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: Príncipe | Statement: [ISO 3166-2:ST, definesSubdivision, Príncipe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Príncipe
Context triple: [ISO 3166-2:ST, definesSubdivision, Príncipe]
  • A. Príncipe chosen
    Príncipe is the smaller, less-populated island of the Central African island nation of São Tomé and Príncipe, known for its lush rainforests, biodiversity, and status as a UNESCO Biosphere Reserve.
  • B. Príncep
    Príncep is the surname of Spanish actor Roger Príncep, known for his role in the film "The Orphanage."
  • C. Prinze
    Prinze is the surname of American actor Freddie Prinze Jr., associated with a family of entertainers in film and television.
  • D. Prinz
    Prinz is a German surname borne by various notable individuals, including figures in politics, religion, and the arts.
  • E. Prence
    Prence is an English surname most notably associated with Thomas Prence, a colonial governor of Plymouth Colony in the 17th century.
  • 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_69d8b9175fec8190af865699b4e64d8c completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e514f3bb888190bdeea4c4d114a43b completed April 19, 2026, 5:46 p.m.
Created at: April 10, 2026, 10:37 a.m.