Triple

T746116
Position Surface form Disambiguated ID Type / Status
Subject St Peter’s Square tram stop E15343 entity
Predicate hasPassengerShelters P3789 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: [St Peter’s Square tram stop, hasPassengerShelters, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasPassengerShelters
Context triple: [St Peter’s Square tram stop, hasPassengerShelters, yes]
  • A. hasShelters chosen
    Indicates that one entity provides, contains, or is associated with one or more shelters for another entity or purpose.
  • B. hasPassengerHandling
    Indicates that an entity is responsible for or involved in managing the processes and services related to handling passengers.
  • C. hasPassengerTerminal
    Indicates that one entity possesses or is equipped with a passenger terminal used for boarding, alighting, or handling passengers.
  • D. closedForPassengers
    Indicates that a transportation facility or vehicle is not available for use by passengers.
  • E. hasRestrooms
    Indicates that a place or facility provides access to restroom or toilet amenities.
  • 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_69a49358aa308190adbc9b5a0a2adcf9 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a62ca1d081908e3191411f86498d completed March 1, 2026, 8:48 p.m.
PD Predicate disambiguation batch_69a4a4ff10608190bfd60b4a1cb38f7d completed March 1, 2026, 8:43 p.m.
Created at: March 1, 2026, 7:37 p.m.