Triple

T21775462
Position Surface form Disambiguated ID Type / Status
Subject CargoNet E537560 entity
Predicate hasKeyRoute P31587 FINISHED
Object Oslo–Trondheim 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: Oslo–Trondheim | Statement: [CargoNet, hasKeyRoute, Oslo–Trondheim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oslo–Trondheim
Context triple: [CargoNet, hasKeyRoute, Oslo–Trondheim]
  • A. Oslo–Trondheim chosen
    Oslo–Trondheim is a major intercity rail route in Norway connecting the capital Oslo with the central city of Trondheim across mountainous inland terrain.
  • B. Trondheim
    Trondheim is a historic Norwegian city in Trøndelag county, known for its medieval Nidaros Cathedral and role as a former capital of Norway.
  • C. Bergens
    The Bergens are a race of gloomy, troll-eating creatures who serve as the primary villains in the animated film "Trolls."
  • D. Oslo
    Oslo is the capital and largest city of Norway, known as a major cultural, economic, and governmental center.
  • E. Oslo
    Oslo is a collection of shared libraries that provide common code and patterns used across various OpenStack projects.
  • 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_69e0c470759c819094a215757113562b completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f046291d808190b5111a8d4819909f completed April 28, 2026, 5:31 a.m.
Created at: April 16, 2026, 6:51 p.m.