Triple

T4086312
Position Surface form Disambiguated ID Type / Status
Subject Split E87591 entity
Predicate hasAirport P105 FINISHED
Object Split Airport E268985 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: Split Airport | Statement: [Split, hasAirport, Split Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Split Airport
Context triple: [Split, hasAirport, Split Airport]
  • A. Split Airport chosen
    Split Airport is an international airport on Croatia’s Dalmatian coast serving the city of Split and the surrounding Adriatic tourist region.
  • B. Flughafen
    Flughafen is the Nuremberg U-Bahn station that serves Nuremberg Airport, providing direct metro access between the airport and the city.
  • C. Aeroport
    Aeroport is a Moscow Metro station on the Zamoskvoretskaya Line, named after the nearby Khodynka Aerodrome area.
  • D. Airport Express
    Airport Express is a high-speed rail service in Hong Kong that links the city center with Hong Kong International Airport.
  • E. Airport line
    The Airport line is a railway service in Brisbane, Australia that connects the city to Brisbane Airport, providing dedicated public transport access for air travelers.
  • 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_69aed94425148190be337845d56fac22 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefc7ceeb48190807f0f5078ccfa12 completed March 9, 2026, 4:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69b56b6335c4819093538f261a5093b3 completed March 14, 2026, 2:06 p.m.
Created at: March 9, 2026, 3:39 p.m.