Triple

T936267
Position Surface form Disambiguated ID Type / Status
Subject City Terminal Zone E20200 entity
Predicate ticketingZoneType P21780 FINISHED
Object terminal zone 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: terminal zone | Statement: [City Terminal Zone, ticketingZoneType, terminal zone]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: ticketingZoneType
Context triple: [City Terminal Zone, ticketingZoneType, terminal zone]
  • A. hasTicketing
    Indicates that an entity provides or is associated with a system or mechanism for issuing, managing, or selling tickets.
  • 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. ticketedAttraction
    Indicates that access to the attraction requires a purchased ticket or paid admission.
  • D. hasFareZone
    Indicates that an entity is located within or associated with a specific fare zone used for pricing or ticketing.
  • E. fareType
    Indicates the category or class of fare (such as standard, discounted, or promotional) that applies to a given trip, ticket, or pricing instance.
  • 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_69a493b0270c81909e6c9ce310f6aa55 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b36558588190a2a9c710073624d1 completed March 1, 2026, 9:45 p.m.
PD Predicate disambiguation batch_69a4b29b245c8190b143f28b77fede3c completed March 1, 2026, 9:41 p.m.
PDg Predicate description generation batch_69a4b326d9d88190913c1a892a795707 completed March 1, 2026, 9:44 p.m.
Created at: March 1, 2026, 7:40 p.m.