Triple

T18597549
Position Surface form Disambiguated ID Type / Status
Subject Midttrafik E454531 entity
Predicate operatesIn P82 FINISHED
Object Holstebro 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: Holstebro | Statement: [Midttrafik, operatesIn, Holstebro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Holstebro
Context triple: [Midttrafik, operatesIn, Holstebro]
  • A. Holstebro chosen
    Holstebro is a town in western Jutland, Denmark, known as a regional center that hosts significant Danish Army military facilities.
  • B. Holbæk
    Holbæk is a coastal town and municipality in northwestern Zealand, Denmark, known for its harbor on Holbæk Fjord and role as a regional commercial and cultural center.
  • C. Vordingborg
    Vordingborg is a historic coastal town in southern Denmark known for the ruins of Vordingborg Castle and its prominent Goose Tower.
  • D. Vejle
    Vejle is a Danish city known for its scenic fjord setting, rolling hills, and role as a regional commercial and transportation hub in southeastern Jutland.
  • E. Horsens
    Horsens is a city in eastern Jutland, Denmark, known historically as a market and industrial town and as the birthplace of explorer Vitus Bering.
  • 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_69d8d38ae7e081908a98df1251842402 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5474d934481909b4afd5ef9031c73 completed April 19, 2026, 9:21 p.m.
Created at: April 10, 2026, 11:44 a.m.