Triple

T23317111
Position Surface form Disambiguated ID Type / Status
Subject Norfolk station E590738 entity
Predicate hasTicketKiosk 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: [Norfolk station, hasTicketKiosk, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasTicketKiosk
Context triple: [Norfolk station, hasTicketKiosk, yes]
  • A. hasTicketBooths
    Indicates that one entity possesses or contains ticket booths used for selling or distributing tickets.
  • B. hasTicketHall
    Indicates that a place or facility includes or is equipped with a designated ticket hall area for purchasing or validating tickets.
  • C. hasTicketInspection
    Indicates that a ticket is checked or verified by an authorized inspector or system.
  • D. hasTicketing
    Indicates that an entity provides or is associated with a system or mechanism for issuing, managing, or selling tickets.
  • E. ticketMachines chosen
    Indicates that there is a relationship involving ticket machines, typically denoting where they are located, available, or associated with a particular entity or place.
  • 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_69e25d1d32188190948eb76909d1dcc3 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f197828c408190ae071624e40de4cc completed April 29, 2026, 5:30 a.m.
PD Predicate disambiguation batch_69effcf8ca2c8190887d4f4656617d21 completed April 28, 2026, 12:19 a.m.
Created at: April 17, 2026, 5:06 p.m.