Triple

T1624594
Position Surface form Disambiguated ID Type / Status
Subject Sale Water Park tram stop E35110 entity
Predicate parkAndRidePurpose P24860 FINISHED
Object intercept car traffic from M60 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: intercept car traffic from M60 | Statement: [Sale Water Park tram stop, parkAndRidePurpose, intercept car traffic from M60]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: parkAndRidePurpose
Context triple: [Sale Water Park tram stop, parkAndRidePurpose, intercept car traffic from M60]
  • A. 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.
  • B. hasParkAndRideGarage
    Indicates that a location includes a parking facility where people can park their vehicles and transfer to public transit services.
  • C. typicalJourneyPurpose
    Indicates the usual or most common reason or objective for which an entity undertakes a journey.
  • D. passesUsedForTransportation
    Indicates that the passes are utilized as a means or instrument for transporting people or goods.
  • E. hasPublicTransportUsage
    Indicates that an entity makes use of, or is associated with the use of, public transportation services.
  • 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_69a886023194819080a3fccd6e325d0e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a9431af5ac8190893133f1ae490142 completed March 5, 2026, 8:47 a.m.
PD Predicate disambiguation batch_69a907c91c888190b6ed295c1a2e0977 completed March 5, 2026, 4:34 a.m.
Created at: March 4, 2026, 7:28 p.m.