Triple

T20088574
Position Surface form Disambiguated ID Type / Status
Subject SCC E496203 entity
Predicate airportName P4100 FINISHED
Object Deadhorse Airport 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: Deadhorse Airport | Statement: [SCC, airportName, Deadhorse Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Deadhorse Airport
Context triple: [SCC, airportName, Deadhorse Airport]
  • A. Deadhorse Airport chosen
    Deadhorse Airport is a remote public airport on Alaska’s North Slope that primarily supports oil field operations and access to the Prudhoe Bay area.
  • B. Lonesome Pine Airport
    Lonesome Pine Airport is a public regional airport serving the Wise, Virginia area and surrounding communities in the Appalachian region.
  • C. Whitegrass Airport
    Whitegrass Airport is the main domestic airport serving the island of Tanna in Vanuatu, providing regional air connections for residents and visitors.
  • D. Herlong Recreational Airport
    Herlong Recreational Airport is a public general aviation airport serving the Jacksonville, Florida area, primarily used for recreational flying and flight training.
  • E. Oakey Airport
    Oakey Airport is a regional airfield in Queensland, Australia, primarily serving general aviation and military training operations.
  • 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_69da626eee3881909f3454986d4a6511 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6655d65a88190a510132f36341b6c completed April 20, 2026, 5:41 p.m.
Created at: April 11, 2026, 11:17 p.m.