Triple

T10628207
Position Surface form Disambiguated ID Type / Status
Subject Fred Gurley E250379 entity
Predicate hasRoute P4374 FINISHED
Object Tomorrowland station E718783 NE 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: Tomorrowland station | Statement: [Fred Gurley, hasRoute, Tomorrowland station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tomorrowland station
Context triple: [Fred Gurley, hasRoute, Tomorrowland station]
  • A. Tomorrowland station chosen
    Tomorrowland station is a themed railroad stop within Disneyland’s Tomorrowland area, serving as one of the stations on the Disneyland Railroad.
  • B. Tomorrowland
    Tomorrowland is a futuristic-themed land found in several Disney parks, featuring attractions and environments inspired by space travel, advanced technology, and visions of the future.
  • C. Tomorrowland
    Tomorrowland is one of the world’s largest and most famous electronic dance music festivals, held annually in Boom, Belgium.
  • D. Tomorrowland Winter
    Tomorrowland Winter is a snow-covered edition of the famous Belgian electronic dance music festival, held annually at a ski resort in the French Alps.
  • E. Tomorrowland (film)
    Tomorrowland is a 2015 science-fiction adventure film directed by Brad Bird that follows a gifted teenager and a disillusioned inventor who discover a futuristic parallel world and attempt to save both it and Earth from impending catastrophe.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d6aa5993448190a493b790b8f85010 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6df9228088190bdd57a95d8671618 completed April 8, 2026, 11:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69d96babc290819096c0c914d038ba01 completed April 10, 2026, 9:29 p.m.
Created at: April 8, 2026, 8:58 p.m.