Triple

T18453479
Position Surface form Disambiguated ID Type / Status
Subject Airport Express Line E450844 entity
Predicate alsoKnownAs P39 FINISHED
Object Orange Line NE NERFINISHED

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: [Airport Express Line, alsoKnownAs, Orange Line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Orange Line
Context triple: [Airport Express Line, alsoKnownAs, Orange Line]
  • A. Orange Line chosen
    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
    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 a route of Portland, Oregon’s MAX Light Rail system that connects downtown Portland with the southeastern suburbs.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d38345688190b565eac2e4cd7935 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5264a49ec8190aa43381d93a55e91 completed April 19, 2026, 7 p.m.
Created at: April 10, 2026, 11:31 a.m.