Triple

T6433680
Position Surface form Disambiguated ID Type / Status
Subject Tokyo Metro 10000 series E129838 entity
Predicate hasLCDPassengerInformationDisplays P3794 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: [Tokyo Metro 10000 series, hasLCDPassengerInformationDisplays, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasLCDPassengerInformationDisplays
Context triple: [Tokyo Metro 10000 series, hasLCDPassengerInformationDisplays, yes]
  • A. hasPassengerInformationSystem
    Indicates that an entity is equipped with a system that provides information to passengers, such as schedules, announcements, or travel updates.
  • B. usedForPassengerInformation
    Indicates that something serves the purpose of providing information to passengers.
  • C. hasDepartureScreens
    Indicates that a location or facility is equipped with screens displaying departure information for services such as trains, buses, or flights.
  • D. hasCustomerInformationScreens chosen
    Indicates that an entity is equipped with screens or displays that present information specifically intended for customers.
  • E. hasRollingStockOnDisplay
    Indicates that a location or entity has railway rolling stock (such as locomotives or carriages) exhibited for public viewing.
  • 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_69c0084caac48190a7bc2ad8ba44536f completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0693f73ec8190883470b57f8141aa completed March 22, 2026, 10:12 p.m.
PD Predicate disambiguation batch_69c060f96980819091bab9335922a457 completed March 22, 2026, 9:36 p.m.
Created at: March 22, 2026, 4:45 p.m.