Triple

T35288352
Position Surface form Disambiguated ID Type / Status
Subject Disneyland Resort tram route E1019151 entity
Predicate hasQueueAreas P3382 FINISHED
Object tram loading queues at parking structures 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: tram loading queues at parking structures | Statement: [Disneyland Resort tram route, hasQueueAreas, tram loading queues at parking structures]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasQueueAreas
Context triple: [Disneyland Resort tram route, hasQueueAreas, tram loading queues at parking structures]
  • A. hasWaitingArea chosen
    Indicates that an entity provides or includes a designated space where people can wait before receiving a service or proceeding to another area.
  • B. queueAreaFeature
    Indicates that a feature or characteristic is associated with, or forms part of, a queue area.
  • C. hasQueue
    Indicates that an entity maintains or is associated with a queue, typically representing an ordered list of items or tasks awaiting processing.
  • D. hasQueueAccessibility
    Indicates that an entity provides accessible features or accommodations for people with disabilities in its queuing or waiting areas.
  • E. queueAreaTheme
    Indicates the thematic style or concept applied to the area where people wait in line for an attraction or service.
  • 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_69f76de6d39c8190bb11342e4b91ff2b completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f7a225a77c81908f8953ccfeb14336 completed May 3, 2026, 7:29 p.m.
PD Predicate disambiguation batch_69f7a06d4f108190bae3ab9ae431d2c7 completed May 3, 2026, 7:22 p.m.
Created at: May 3, 2026, 4:03 p.m.