Triple

T5250852
Position Surface form Disambiguated ID Type / Status
Subject St. James station E118581 entity
Predicate ticketMachines P61741 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: [St. James station, ticketMachines, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: ticketMachines
Context triple: [St. James station, ticketMachines, yes]
  • A. hasTicketBooths
    Indicates that one entity possesses or contains ticket booths used for selling or distributing tickets.
  • B. ticketingLocation
    Indicates the place or point where tickets are issued, sold, or otherwise processed for an event, service, or journey.
  • 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. sellsTicketsUnder
    Indicates that one entity sells tickets at a price lower than or under the pricing of another entity.
  • 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. chosen

Provenance (4 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_69bd446978108190bb5f9c5c23d93f88 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7b79ae0c81908a9b8614f6886259 completed March 20, 2026, 4:53 p.m.
PD Predicate disambiguation batch_69bd77c30bac8190a883ca45da35d667 completed March 20, 2026, 4:37 p.m.
PDg Predicate description generation batch_69bd787975788190848ffbac87896efe completed March 20, 2026, 4:40 p.m.
Created at: March 20, 2026, 1:50 p.m.