Triple

T1632457
Position Surface form Disambiguated ID Type / Status
Subject Miami station E35285 entity
Predicate hasPassengerBuilding P1711 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: [Miami station, hasPassengerBuilding, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasPassengerBuilding
Context triple: [Miami station, hasPassengerBuilding, yes]
  • A. hasPassengerTerminal
    Indicates that one entity possesses or is equipped with a passenger terminal used for boarding, alighting, or handling passengers.
  • B. hasPassengerTerminalDesign
    Indicates a design relationship in which one entity specifies or defines the passenger terminal layout, structure, or configuration of another entity.
  • C. hasStationBuilding chosen
    Indicates that a station is associated with or includes a station building as part of its facilities.
  • D. hasPassengerHandling
    Indicates that an entity is responsible for or involved in managing the processes and services related to handling passengers.
  • E. hasPassengerServicesTo
    Indicates that a transportation provider operates passenger services connecting one location or entity to another.
  • 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_69a886036bc081909ff5de16dbe5e8ea 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.