Triple

T17244425
Position Surface form Disambiguated ID Type / Status
Subject MARTA rail stations E418584 entity
Predicate hasLine P35 FINISHED
Object Red Line E115430 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: Red Line | Statement: [MARTA rail stations, hasLine, Red Line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Red Line
Context triple: [MARTA rail stations, hasLine, Red Line]
  • A. Red Line chosen
    The Red Line is one of the primary heavy-rail rapid transit routes in Atlanta’s MARTA system, running north–south and serving key destinations across the metropolitan area.
  • B. Red Line
    Red Line is one of the main rapid transit routes of the Dubai Metro, running along key areas of the city and serving many of its major commercial and residential districts.
  • C. Red Line
    The Red Line is a primary route of the MetroLink light rail system serving key destinations in the St. Louis metropolitan area.
  • D. Red Line
    The Red Line is one of the main lines of the Stockholm metro system, running from Norsborg and Fruängen in the southwest through central Stockholm to several northeastern suburbs.
  • E. Red Line
    Red Line is a 1996 American action film starring Jan-Michael Vincent, centered on illegal street racing and high-speed car chases.
  • 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_69d886d8e96081909870bff6c3d0bf09 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42e22fb2c8190aea5d3872095bf46 completed April 19, 2026, 1:21 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0180ca18c081909ef80a4056b3dbf7 completed May 11, 2026, 7:10 a.m.
Created at: April 10, 2026, 5:39 a.m.