Triple

T531017
Position Surface form Disambiguated ID Type / Status
Subject Beijing Subway E12220 entity
Predicate ticketInspection P1740 FINISHED
Object automatic fare collection gates 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: automatic fare collection gates | Statement: [Beijing Subway, ticketInspection, automatic fare collection gates]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: ticketInspection
Context triple: [Beijing Subway, ticketInspection, automatic fare collection gates]
  • A. ticketingCompatibleWith
    Indicates that two systems, services, or components can interoperate or be used together within the same ticketing or reservation workflow without conflict.
  • B. ticketedAttraction
    Indicates that access to the attraction requires a purchased ticket or paid admission.
  • C. hasTicketing
    Indicates that an entity provides or is associated with a system or mechanism for issuing, managing, or selling tickets.
  • D. hasTicketRequirement
    Indicates that an entity is subject to a specific ticket or admission requirement in order for access, participation, or use to be allowed.
  • E. fareControl chosen
    Indicates that an entity is responsible for monitoring, enforcing, or managing payment of fares for access to a service or facility.
  • 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_69a4933208e88190891f5debab1b776d completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4985e51908190a34aa82ea9dbee1e completed March 1, 2026, 7:49 p.m.
PD Predicate disambiguation batch_69a494b257108190a537dffbb9d621b5 completed March 1, 2026, 7:34 p.m.
Created at: March 1, 2026, 7:32 p.m.