Triple

T4631325
Position Surface form Disambiguated ID Type / Status
Subject Glenside station E101422 entity
Predicate ticketOffice P43373 FINISHED
Object yes 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: yes | Statement: [Glenside station, ticketOffice, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: ticketOffice
Context triple: [Glenside station, ticketOffice, yes]
  • A. ticketDemand
    Indicates that there is a level of desire or need among potential buyers for tickets to an event, service, or offering.
  • B. ticketClass
    Indicates the category or level of service assigned to a ticket within a ticketing or reservation system.
  • C. ticketingProduct
    Indicates a relationship where an entity is associated with, or offered as, a ticketing-related product (such as a service or item used for issuing, managing, or selling tickets).
  • D. ticketingLocation chosen
    Indicates the place or point where tickets are issued, sold, or otherwise processed for an event, service, or journey.
  • E. ticketingCompatibleWith
    Indicates that two systems, services, or components can interoperate or be used together within the same ticketing or reservation workflow without conflict.
  • 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_69bd43d2f1c081908cd4b7ec48ecc73d completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd5a32d6408190962e60b9bce7560d completed March 20, 2026, 2:31 p.m.
PD Predicate disambiguation batch_69bd5233cb5081908807e2b150f0ca06 completed March 20, 2026, 1:57 p.m.
Created at: March 20, 2026, 1:13 p.m.