Triple

T30663346
Position Surface form Disambiguated ID Type / Status
Subject Air Canada Signature Class E780590 entity
Predicate entertainmentFeature P19394 FINISHED
Object personal seatback entertainment screen 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: personal seatback entertainment screen | Statement: [Air Canada Signature Class, entertainmentFeature, personal seatback entertainment screen]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: entertainmentFeature
Context triple: [Air Canada Signature Class, entertainmentFeature, personal seatback entertainment screen]
  • A. entertainmentFocus
    Indicates that one entity is primarily concerned with, directed toward, or centered on providing or engaging in entertainment for another entity or context.
  • B. entertainmentType
    Indicates the kind or category of entertainment associated with an entity or event.
  • C. specialFeature chosen
    Indicates that an entity possesses a distinctive or noteworthy attribute, capability, or characteristic that sets it apart from others.
  • D. festivalFeature
    Indicates that a festival includes or showcases a particular element, activity, or attraction as one of its features.
  • E. filmContent
    Indicates that one entity is the substantive material or subject matter contained within a film.
  • 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_69f224a6d10481909290be1a00fc83b3 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f6df450014819099d118e5c2d697fa completed May 3, 2026, 5:38 a.m.
PD Predicate disambiguation batch_69f6de07836481908785cde9c511920b completed May 3, 2026, 5:32 a.m.
Created at: April 29, 2026, 8:31 p.m.