Triple

T4177149
Position Surface form Disambiguated ID Type / Status
Subject Calgary CTrain E86504 entity
Predicate hasLine P35 FINISHED
Object Blue Line
The Blue Line is one of the primary light rail transit routes in Calgary's CTrain system, serving key corridors across the city.
E438547 NE FINISHED

How this triple was built (4 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: Blue Line | Statement: [Calgary CTrain, hasLine, Blue Line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Blue Line
Context triple: [Calgary CTrain, hasLine, Blue Line]
  • A. Blue Line
    The Blue Line is one of the color-coded rapid transit routes in the Washington Metro system, running through key parts of Washington, D.C. and its Virginia suburbs.
  • B. Blue Line
    The Blue Line is one of Boston's MBTA rapid transit routes, running primarily between downtown Boston and the coastal communities of East Boston and Revere.
  • C. Blue Line
    The Blue Line is one of the main lines of the Lisbon Metro system, serving key central and northern areas of Portugal’s capital city.
  • D. Blue Line
    The Blue Line is one of the main rapid transit corridors of the Hyderabad Metro system in Hyderabad, India.
  • E. Blue Line
    The Blue Line is one of the Montreal Metro’s rapid transit lines, running east–west to serve several central and northeastern neighborhoods of the city.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Blue Line
Triple: [Calgary CTrain, hasLine, Blue Line]
Generated description
The Blue Line is one of the primary light rail transit routes in Calgary's CTrain system, serving key corridors across the city.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Blue Line
Target entity description: The Blue Line is one of the primary light rail transit routes in Calgary's CTrain system, serving key corridors across the city.
  • A. Blue Line
    Blue Line is a light rail service route within Salt Lake City’s TRAX public transit system, connecting key areas of the metropolitan region.
  • B. Blue Line
    The Blue Line is a light rail route in the Dallas Area Rapid Transit (DART) system serving key neighborhoods and suburbs in the Dallas–Fort Worth metroplex.
  • C. Blue Line
    The Blue Line is a primary route of the Baltimore Light Rail system that provides north–south rail transit service through the Baltimore metropolitan area.
  • D. Blue Line
    The Blue Line is a light rail service operated by Sacramento Regional Transit that runs through key corridors of the Sacramento metropolitan area.
  • E. Blue Line
    The Blue Line is one of the major corridors of the Delhi Metro rapid transit system, connecting key residential and commercial areas across Delhi and its neighboring regions.
  • F. None of above. chosen

Provenance (5 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_69aed93de98c8190ad838ce507b77c8a completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af02ec20fc8190b6f30576337e0ddc completed March 9, 2026, 5:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5f5ad18e881909950d8f45912fad5 completed March 14, 2026, 11:56 p.m.
NEDg Description generation batch_69b5f65e9bec819082c33b0c066cd42b completed March 14, 2026, 11:59 p.m.
NED2 Entity disambiguation (via description) batch_69b5fa90f6a48190a27dfeb65f705225 completed March 15, 2026, 12:17 a.m.
Created at: March 9, 2026, 3:45 p.m.