Triple

T13715748
Position Surface form Disambiguated ID Type / Status
Subject C09 E328892 entity
Predicate ticketingUse P38658 FINISHED
Object station identification 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: station identification | Statement: [C09, ticketingUse, station identification]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: ticketingUse
Context triple: [C09, ticketingUse, station identification]
  • A. ticketingScope
    Indicates the range or domain within which ticketing actions (such as creation, assignment, or management of tickets) are valid or applicable.
  • B. ticketingCompatibleWith
    Indicates that two systems, services, or components can interoperate or be used together within the same ticketing or reservation workflow without conflict.
  • C. usedInE-tickets chosen
    Indicates that something (such as a method, technology, or feature) is employed or applied within the context of electronic tickets (e-tickets).
  • D. hasTicketing
    Indicates that an entity provides or is associated with a system or mechanism for issuing, managing, or selling tickets.
  • E. ticketingIssue
    Indicates that there is a problem, error, or complication related to a ticketing process or ticket-based 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_69d80770b9bc81909f70c8c317d53cff completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dd43973cf08190a417d0cca9dd314a completed April 13, 2026, 7:27 p.m.
PD Predicate disambiguation batch_69dbbe92d77c81908e0244cffb7f78c5 completed April 12, 2026, 3:47 p.m.
Created at: April 9, 2026, 9:54 p.m.