Triple

T1624447
Position Surface form Disambiguated ID Type / Status
Subject Peel Hall tram stop E35106 entity
Predicate onLine P1293 FINISHED
Object Airport Line E5769 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: [Peel Hall tram stop, onLine, Airport Line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Airport Line
Context triple: [Peel Hall tram stop, onLine, Airport Line]
  • A. Airport Line chosen
    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
    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.
  • C. Airport Line
    Airport Line is a SEPTA Regional Rail service in the Philadelphia area that connects Center City with Philadelphia International Airport.
  • 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. Flughafen
    Flughafen is the Nuremberg U-Bahn station that serves Nuremberg Airport, providing direct metro access between the airport and the city.
  • 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_69a886023194819080a3fccd6e325d0e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a909d0586c81909e399b636e130ff5 completed March 5, 2026, 4:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad58ccc80c819088ecd91f0a99a247 completed March 8, 2026, 11:09 a.m.
Created at: March 4, 2026, 7:28 p.m.