Triple

T18735739
Position Surface form Disambiguated ID Type / Status
Subject Metropark station E458156 entity
Predicate parkAndRideFacility P24860 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: [Metropark station, parkAndRideFacility, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: parkAndRideFacility
Context triple: [Metropark station, parkAndRideFacility, yes]
  • A. transportationFacility
    Indicates that one entity is a facility or location used for the transportation or transit of people or goods in relation to another entity.
  • B. hasParkAndRideFunction chosen
    Indicates that a location or facility serves as a park-and-ride, where people can park vehicles and transfer to another mode of transport for the rest of their journey.
  • C. parkSystem
    Indicates a relationship where an entity is part of, managed by, or associated with an organized system of parks or protected recreational areas.
  • D. hasParkAndRideGarage
    Indicates that a location includes a parking facility where people can park their vehicles and transfer to public transit services.
  • E. parkingStructure
    Indicates that one entity is a parking facility or structure associated with another entity (such as a building, location, or organization).
  • 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_69d8d394dc308190b6725073f5db324c completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e56d7ae10081908bc6857d1d147eef completed April 20, 2026, 12:04 a.m.
PD Predicate disambiguation batch_69e48d03766c8190a43f7681842f4f8d completed April 19, 2026, 8:06 a.m.
Created at: April 10, 2026, 11:51 a.m.