Triple

T37416129
Position Surface form Disambiguated ID Type / Status
Subject Cyberjaya Utara MRT station E929713 entity
Predicate hasUnpaidAreaConcourse P194541 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: [Cyberjaya Utara MRT station, hasUnpaidAreaConcourse, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasUnpaidAreaConcourse
Context triple: [Cyberjaya Utara MRT station, hasUnpaidAreaConcourse, yes]
  • A. hasUnpaidAreaTransfer
    Indicates that an area transfer between entities has occurred for which the corresponding payment has not yet been made.
  • B. hasTicketConcourse
    Indicates that an entity is associated with or located in a ticket concourse area.
  • C. hasFarePaidArea
    Indicates that an entity includes or is associated with a zone where access is restricted to users who have paid a fare.
  • D. hasTicketedArea
    Indicates that an area is restricted to individuals who possess a valid ticket or fare authorization.
  • E. hasReservationArea
    Indicates that an entity is assigned or associated with a specific reserved area or section designated for its use.
  • 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_69f76ebde49481908566cd96b37ccc84 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fd783fed9c81909e792702636c4f1f completed May 8, 2026, 5:44 a.m.
PD Predicate disambiguation batch_69fd7788e63c81909de22fdafcfe41c0 completed May 8, 2026, 5:41 a.m.
PDg Predicate description generation batch_69fd783e9e5c819087dec7fefa03700d completed May 8, 2026, 5:44 a.m.
Created at: May 3, 2026, 4:16 p.m.