Triple

T27747297
Position Surface form Disambiguated ID Type / Status
Subject Oak Street station E702018 entity
Predicate hasParkAndRideType P24862 FINISHED
Object surface lot 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: surface lot | Statement: [Oak Street station, hasParkAndRideType, surface lot]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasParkAndRideType
Context triple: [Oak Street station, hasParkAndRideType, surface lot]
  • A. hasParkAndRideFunction
    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.
  • B. hasParkAndRideGarage chosen
    Indicates that a location includes a parking facility where people can park their vehicles and transfer to public transit services.
  • C. hasPublicTransitMode
    Indicates that a location, route, or service is associated with or supports a specific mode of public transportation (e.g., bus, train, tram).
  • D. hasPublicTransitFunction
    Indicates that something serves a role or provides a service related to public transportation operations or infrastructure.
  • E. hasPublicTransitCoverageType
    Indicates the type or category of public transit service coverage associated with an entity.
  • 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_69ef6a53c7388190899baa6daf42301c completed April 27, 2026, 1:53 p.m.
NER Named-entity recognition batch_69fb3425666081908916fcbf3b5dd907 completed May 6, 2026, 12:29 p.m.
PD Predicate disambiguation batch_69fb2f5f3164819099429c2cc3d24e01 completed May 6, 2026, 12:09 p.m.
Created at: April 27, 2026, 4:17 p.m.