Triple

T13316641
Position Surface form Disambiguated ID Type / Status
Subject Osaka Marriott Miyako Hotel E317203 entity
Predicate hasExecutiveLounge P13530 FINISHED
Object true LITERAL 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: true | Statement: [Osaka Marriott Miyako Hotel, hasExecutiveLounge, true]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasExecutiveLounge
Context triple: [Osaka Marriott Miyako Hotel, hasExecutiveLounge, true]
  • A. hasCustomerLounge chosen
    Indicates that an entity provides or includes a designated lounge area for customers to use.
  • B. hasLoungeCar
    Indicates that something includes or is equipped with a lounge car as part of its composition or configuration.
  • C. hasLoungeType
    Indicates that an entity is associated with, or classified by, a particular type or category of lounge.
  • D. hasPrioritySeating
    Indicates that one entity provides or designates reserved or preferential seating for another entity.
  • E. hasPassengerCheckInAccess
    Indicates that an entity is permitted to perform or access passenger check-in functions for a given transport service or location.
  • 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_69d806b4d62c81908d4ced1665414be5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99cfdc9388190af1fdd3cd4717bd8 completed April 11, 2026, 12:59 a.m.
PD Predicate disambiguation batch_69d98f6babd88190a5d529df9584b9a4 completed April 11, 2026, 12:01 a.m.
Created at: April 9, 2026, 9:29 p.m.