Triple

T23126790
Position Surface form Disambiguated ID Type / Status
Subject Oslo Tunnel E577053 entity
Predicate connects P390 FINISHED
Object Nationaltheatret Station 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: Nationaltheatret Station | Statement: [Oslo Tunnel, connects, Nationaltheatret Station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nationaltheatret Station
Context triple: [Oslo Tunnel, connects, Nationaltheatret Station]
  • A. Nationaltheatret station chosen
    Nationaltheatret station is a major underground transport hub in central Oslo that serves both metro and railway lines, connecting key parts of the city and surrounding region.
  • B. Bella Center station
    Bella Center station is a Copenhagen Metro stop serving the Bella Center convention and exhibition complex on the island of Amager.
  • C. Nørreport station
    Nørreport station is one of Copenhagen’s busiest central transport hubs, serving as a major interchange for metro, regional, and S-train services.
  • D. Frederiksberg Station
    Frederiksberg Station is a key Copenhagen Metro and S-train interchange located in the Frederiksberg district of Denmark’s capital.
  • E. Drammen Station
    Drammen Station is a major railway hub in Drammen, Norway, connecting regional and long-distance train services to Oslo and other parts of the country.
  • 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_69e245f7b0e481909c473ff4e6a54e2c completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f18e5482588190b95b36075ecc7f24 completed April 29, 2026, 4:51 a.m.
Created at: April 17, 2026, 3:59 p.m.