Triple

T16777765
Position Surface form Disambiguated ID Type / Status
Subject Bonaventure station E407772 entity
Predicate line P1293 FINISHED
Object Orange Line E435552 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: Orange Line | Statement: [Bonaventure station, line, Orange Line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Orange Line
Context triple: [Bonaventure station, line, Orange Line]
  • A. Orange Line
    The Orange Line is a major corridor of the Delhi Metro system that connects central Delhi to the Indira Gandhi International Airport and surrounding areas.
  • B. Orange Line chosen
    The Orange Line is one of the primary rapid transit routes in Montreal’s Metro system, running in a U-shaped corridor that connects several major residential and commercial districts across the city.
  • C. Orange Line
    The Orange Line is a rapid transit line in the Kaohsiung Mass Rapid Transit (KMRT) system in Kaohsiung, Taiwan.
  • D. Orange Line
    The Orange Line is one of the primary rapid transit routes in the Washington Metro system, running east–west through Washington, D.C. and its Virginia and Maryland suburbs.
  • E. Orange Line
    The Orange Line is a rapid transit route in Chicago that connects the city's Loop with Midway International Airport as part of the Chicago "L" 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_69d8839270588190886720d9519bbf8f completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3b212fc248190a8fe1124853bf16d completed April 18, 2026, 4:32 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00aae0f87c819085ebc7d475ebe8ba completed May 10, 2026, 3:57 p.m.
Created at: April 10, 2026, 5:22 a.m.