Triple

T20030128
Position Surface form Disambiguated ID Type / Status
Subject Gold Line (MARTA) E495098 entity
Predicate hasStation P35 FINISHED
Object North Avenue station NE NERFINISHED

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: North Avenue station | Statement: [Gold Line (MARTA), hasStation, North Avenue station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: North Avenue station
Context triple: [Gold Line (MARTA), hasStation, North Avenue station]
  • A. North Avenue station
    North Avenue station is a transit stop on Baltimore's Light Rail system serving the North Avenue corridor in Baltimore, Maryland.
  • B. North Avenue station
    North Avenue station is a major elevated rail station in Quezon City, Philippines, serving as a key commuter hub on Manila’s MRT Line 3.
  • C. North Avenue station chosen
    North Avenue station is a rapid transit stop in Atlanta, Georgia, serving MARTA’s Red Line near the city’s Midtown and downtown areas.
  • D. Forest Avenue station
    Forest Avenue station is a New York City Subway stop on the M line located in the Ridgewood neighborhood of Queens.
  • E. Snelling Avenue Station
    Snelling Avenue Station is a light rail stop in Saint Paul, Minnesota, serving the METRO Green Line and providing access to nearby neighborhoods and commercial areas.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da626bfd288190aa5d65098b6433ae completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66291a00c8190b0b895909f32d623 completed April 20, 2026, 5:29 p.m.
Created at: April 11, 2026, 3:36 p.m.