Triple

T16442247
Position Surface form Disambiguated ID Type / Status
Subject CTA rail network E399332 entity
Predicate hasLine P35 FINISHED
Object Pink Line E18388 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: Pink Line | Statement: [CTA rail network, hasLine, Pink Line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pink Line
Context triple: [CTA rail network, hasLine, Pink Line]
  • A. Pink Line chosen
    The Pink Line is a rapid transit route in Chicago's "L" system that runs between the Loop and the city's West Side neighborhoods.
  • B. Pink Line
    Pink Line is a major corridor of the Delhi Metro network that forms part of the system’s orbital route around the city.
  • C. Pink Line
    The Pink Line is an elevated mass transit monorail route in Bangkok that serves as part of the city's urban rail network, connecting northern and eastern suburbs.
  • 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
    The Red Line is a regional express bus route operated under the SolanoExpress system, providing intercity transit service in Solano County and surrounding areas.
  • 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_69d87f2c6778819080fcfae53be8f12a completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32ba91dc48190bc35db60f63d36d3 completed April 18, 2026, 6:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0060746c308190b67ff7c4646e10de completed May 10, 2026, 10:39 a.m.
Created at: April 10, 2026, 5:10 a.m.