Triple

T14056899
Position Surface form Disambiguated ID Type / Status
Subject City Circle Line E338241 entity
Predicate owner P347 FINISHED
Object Metroselskabet E339370 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: Metroselskabet | Statement: [City Circle Line, owner, Metroselskabet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Metroselskabet
Context triple: [City Circle Line, owner, Metroselskabet]
  • A. Metroselskabet I/S chosen
    Metroselskabet I/S is the publicly owned company responsible for developing, expanding, and overseeing the Copenhagen Metro system in Denmark.
  • B. Metros
    Metros is the nickname historically used for the MetroStars, the former Major League Soccer team now known as the New York Red Bulls.
  • C. T-bane
    T-bane is the rapid transit metro system serving Oslo and parts of its surrounding metropolitan area in Norway.
  • D. Copenhagen Metro
    Copenhagen Metro is a rapid transit system in Copenhagen, Denmark, known for its driverless trains, frequent service, and extensive underground and elevated lines connecting key parts of the city and suburbs.
  • E. Metropolitana
    Metropolitana is the principal coastal metropolitan region of the Brazilian state of Espírito Santo, encompassing its capital and surrounding urban 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_69d81c67ba6c819091935650dfb3b895 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de3c8e6d008190af8892f34c5cefbd completed April 14, 2026, 1:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd1930da6481908d17adc6f7bbedd4 completed May 7, 2026, 10:58 p.m.
Created at: April 9, 2026, 10:20 p.m.