Triple

T12786490
Position Surface form Disambiguated ID Type / Status
Subject Saint Barts E305640 entity
Predicate airport P1065 FINISHED
Object Gustaf III Airport E305644 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: Gustaf III Airport | Statement: [Saint Barts, airport, Gustaf III Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gustaf III Airport
Context triple: [Saint Barts, airport, Gustaf III Airport]
  • A. Gustaf III Airport chosen
    Gustaf III Airport is the small, short-runway airport serving the Caribbean island of Saint Barthélemy, known for its challenging approach and dramatic landings close to a beach.
  • B. Norrköping Airport
    Norrköping Airport is a regional airport in Norrköping, Sweden, serving domestic and limited international flights for the surrounding area.
  • C. Ronneby Airport
    Ronneby Airport is a regional airport in southern Sweden serving the Ronneby and Blekinge area with domestic flights and operated as part of the national airport network.
  • D. Jönköping Airport
    Jönköping Airport is a regional airport in southern Sweden serving the city of Jönköping with domestic and limited international flights.
  • E. Uppsala Airport
    Uppsala Airport is a Swedish airfield near the city of Uppsala, primarily used for military and general aviation rather than large-scale commercial passenger traffic.
  • 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_69d7bdf2b43c819098ae5aa68e61ea58 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96e5dbdb88190a1b06721ada51627 completed April 10, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6850703948190984acf9e434cd2a7 completed May 2, 2026, 11:13 p.m.
Created at: April 9, 2026, 5:29 p.m.