Triple

T17422268
Position Surface form Disambiguated ID Type / Status
Subject Wasilla, Alaska E423644 entity
Predicate hasAirport P105 FINISHED
Object Wasilla 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: Wasilla Airport | Statement: [Wasilla, Alaska, hasAirport, Wasilla Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wasilla Airport
Context triple: [Wasilla, Alaska, hasAirport, Wasilla Airport]
  • A. Wasilla Airport chosen
    Wasilla Airport is a public general aviation airport serving the city of Wasilla in Alaska, United States.
  • B. E. T. Joshua Airport
    E. T. Joshua Airport was the former main airport serving Saint Vincent and the Grenadines before being replaced by Argyle International Airport.
  • C. Muanda Airport
    Muanda Airport is a public airport serving the coastal town of Muanda in the western Democratic Republic of the Congo, providing regional air connectivity for passengers and cargo.
  • D. Fascene Airport
    Fascene Airport is the main international airport serving the island of Nosy Be in northwestern Madagascar, handling both domestic and tourist flights.
  • E. Sky Harbor Airport
    Sky Harbor Airport is a major international airport serving the Phoenix metropolitan area in Arizona and one of the busiest air travel hubs in the United States.
  • 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_69d889d88b6081908bada047f5b3ba51 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e44237f2cc819083ca0e7e00d828fb completed April 19, 2026, 2:47 a.m.
Created at: April 10, 2026, 5:46 a.m.