Triple

T9804619
Position Surface form Disambiguated ID Type / Status
Subject ER3 E237922 entity
Predicate aircraftSeatingClass P84520 FINISHED
Object regional capacity 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: regional capacity | Statement: [ER3, aircraftSeatingClass, regional capacity]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: aircraftSeatingClass
Context triple: [ER3, aircraftSeatingClass, regional capacity]
  • A. seatClass
    Indicates the travel or seating category assigned to a passenger or seat (e.g., economy, business, first class).
  • B. aircraftSeatingCategory chosen
    Indicates the classification of an aircraft’s seating arrangement or capacity type associated with an entity.
  • C. classesOfSeats
    Indicates the different categories or types of seats associated with something, such as a venue, vehicle, or event.
  • D. seatCategory
    Indicates the classification or type of a seat (e.g., by comfort level, price tier, or section) assigned to an entity.
  • E. ticketClass
    Indicates the category or level of service assigned to a ticket within a ticketing or reservation system.
  • 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_69ca84dd4608819097ff4ed00feca280 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdab7a0ce881908f0555d194dece3f completed April 1, 2026, 11:34 p.m.
PD Predicate disambiguation batch_69cd03dd2da881909052fbf29736a773 completed April 1, 2026, 11:39 a.m.
Created at: March 30, 2026, 8:29 p.m.