Triple

T17310779
Position Surface form Disambiguated ID Type / Status
Subject Airport Transit System E420287 entity
Predicate hasStation P35 FINISHED
Object Terminal 2 station E1197085 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: Terminal 2 station | Statement: [Airport Transit System, hasStation, Terminal 2 station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Terminal 2 station
Context triple: [Airport Transit System, hasStation, Terminal 2 station]
  • A. Terminal 2 station
    Terminal 2 station is a metro stop on Beijing’s Capital Airport Express line serving Terminal 2 of Beijing Capital International Airport.
  • B. Terminal 2 station chosen
    Terminal 2 station is an AirTrain people-mover stop serving passengers at Terminal 2 of San Francisco International Airport.
  • C. Terminal 3 station
    Terminal 3 station is an AirTrain people-mover stop serving the Terminal 3 area at San Francisco International Airport.
  • D. Airport Terminal 2 Station
    Airport Terminal 2 Station is a metro station on the Taoyuan Airport MRT line in Taiwan that serves passengers traveling to and from Taoyuan International Airport’s Terminal 2.
  • E. Terminal 2 East
    Terminal 2 East is one of the concourses at San Diego International Airport’s Terminal 2, serving a selection of the airport’s domestic and international flights.
  • 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_69d889d22b848190a4663d0b8f8f76e7 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e4399837b08190b7cf74201b3cb013 completed April 19, 2026, 2:10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0180e5043081908f31c2434e9b9647 completed May 11, 2026, 7:10 a.m.
Created at: April 10, 2026, 5:43 a.m.