Triple

T3752115
Position Surface form Disambiguated ID Type / Status
Subject Howard E81355 entity
Predicate servedByLine P1293 FINISHED
Object Red Line E15830 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: [Howard, servedByLine, Red Line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Red Line
Context triple: [Howard, servedByLine, Red Line]
  • A. Red Line
    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 was the original name of Los Angeles Metro’s B Line, a heavy-rail subway corridor serving key neighborhoods between Downtown Los Angeles and North Hollywood.
  • C. 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.
  • D. Red Line
    The Red Line is a primary route of the MetroLink light rail system serving key destinations in the St. Louis metropolitan area.
  • E. Red Line chosen
    The Red Line is a major rapid transit route in Chicago that runs north–south through the city, serving as one of the busiest lines in its subway and elevated rail system.
  • 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_69ad8b19b7b08190a6188804e99c53e9 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcb92135c819093f6d616d3ad28ff completed March 8, 2026, 7:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69b51203d6148190a9946a3f274e21a5 completed March 14, 2026, 7:45 a.m.
Created at: March 8, 2026, 3:35 p.m.