Triple

T16277601
Position Surface form Disambiguated ID Type / Status
Subject Wayne Junction E395173 entity
Predicate servesLine P839 FINISHED
Object Airport Line E16837 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: Airport Line | Statement: [Wayne Junction, servesLine, Airport Line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Airport Line
Context triple: [Wayne Junction, servesLine, Airport Line]
  • A. Airport Line
    The Airport Line is a Manchester Metrolink light rail route that connects central Manchester with Manchester Airport, serving key suburbs and transport interchanges along the way.
  • B. Airport Line chosen
    Airport Line is a SEPTA Regional Rail service in the Philadelphia area that connects Center City with Philadelphia International Airport.
  • C. Airport Line
    Airport Line is a Wuhan Metro route that connects the city’s urban rail network with its main airport, providing rapid transit access for air travelers.
  • D. Airport Line
    Airport Line is a railway line in Japan that connects urban areas to Kansai International Airport, operated by the private Nankai Electric Railway company.
  • E. Airport line
    The Airport line is a railway service in Brisbane, Australia that connects the city to Brisbane Airport, providing dedicated public transport access for air travelers.
  • 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_69d87f22c7248190a54c949738441e2e completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2460f73648190b5c931f2ba2a09da completed April 17, 2026, 2:39 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0017c2b9688190b96d62d83a03f158 completed May 10, 2026, 5:29 a.m.
Created at: April 10, 2026, 5:05 a.m.