Triple

T2177133
Position Surface form Disambiguated ID Type / Status
Subject Concourse A Station E48554 entity
Predicate hasService P182 FINISHED
Object AeroTrain E4424 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: AeroTrain | Statement: [Concourse A Station, hasService, AeroTrain]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: AeroTrain
Context triple: [Concourse A Station, hasService, AeroTrain]
  • A. AeroTrain chosen
    AeroTrain is an automated underground people mover system that transports passengers between terminals at Washington Dulles International Airport.
  • B. O-Train
    The O-Train is Ottawa’s urban rail transit system, providing light rail service across key corridors of Canada’s capital city.
  • C. Sky-Streak cabin monorail
    The Sky-Streak cabin monorail was a futuristic elevated transportation ride that showcased modern transit technology to visitors at the New York World's Fair.
  • D. Alweg Monorail
    The Alweg Monorail is an elevated monorail system in Seattle that became an iconic symbol of mid-20th-century futuristic transportation design.
  • E. AirTrain Newark
    AirTrain Newark is an automated monorail system that connects Newark Liberty International Airport’s terminals with parking areas and regional rail services.
  • 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_69a88aa3faa48190995b233af6525815 completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abbeecdbc881909982a58568f0b1ed completed March 7, 2026, 6 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae653de18481909c3521e060540a38 completed March 9, 2026, 6:14 a.m.
Created at: March 4, 2026, 7:45 p.m.