Triple

T23139926
Position Surface form Disambiguated ID Type / Status
Subject Queenstown Airport E577430 entity
Predicate locatedIn P40 FINISHED
Object Frankton 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: Frankton | Statement: [Queenstown Airport, locatedIn, Frankton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Frankton
Context triple: [Queenstown Airport, locatedIn, Frankton]
  • A. Frankton chosen
    Frankton is a lakeside suburb of Queenstown in New Zealand’s South Island, situated on the shores of Lake Wakatipu and known for its residential areas and proximity to the region’s main airport.
  • B. Noisseville
    Noisseville is a commune in northeastern France, near Metz in the Moselle department, known historically as the site of a major Franco-Prussian War battle.
  • C. Fullerville
    Fullerville is a historic mill village and former industrial community that is now a notable historic site within Villa Rica, Georgia.
  • D. Leudeville
    Leudeville is a small commune in the Essonne department of the Île-de-France region in northern France.
  • E. Tailleville
    Tailleville is a small commune in the Calvados department of the Normandy region in northwestern France.
  • 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_69e245f8e6248190ba3d58e068b4dccb completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f18ec922b481908084eee6a95aef83 completed April 29, 2026, 4:53 a.m.
Created at: April 17, 2026, 4 p.m.