Triple

T38183214
Position Surface form Disambiguated ID Type / Status
Subject Hanamaki E1005231 entity
Predicate hasAlternateAirportName P22570 FINISHED
Object Iwate Hanamaki 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: Iwate Hanamaki Airport | Statement: [Hanamaki, hasAlternateAirportName, Iwate Hanamaki Airport]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasAlternateAirportName
Context triple: [Hanamaki, hasAlternateAirportName, Iwate Hanamaki Airport]
  • A. airportAlsoKnownAs chosen
    Indicates that an airport is referred to by an alternative name or alias in addition to its primary name.
  • B. hasFormerNearbyAirportName
    Indicates that an entity previously had a nearby airport known by a different name than its current nearby airport name.
  • C. hasSecondaryAirport
    Indicates that an entity is associated with an additional, typically smaller or alternative, airport beyond its primary one.
  • D. hasAlternativeNameForSameCity
    Indicates that one city name is an alternative or variant name referring to the same city as another name.
  • E. destinationAirportAlternativeName
    Indicates that an airport serves as an alternative or secondary destination for another airport, typically used when the primary destination is unavailable or unsuitable.
  • F. None of above.

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_69f76dbc22c481908139b694ffde7a0c completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69fe96c2647c819082989f11e1ae3d35 completed May 9, 2026, 2:06 a.m.
PD Predicate disambiguation batch_69fe928615448190af939e5a94be55bb completed May 9, 2026, 1:48 a.m.
Created at: May 3, 2026, 4:29 p.m.