Triple

T10852222
Position Surface form Disambiguated ID Type / Status
Subject Herning Station E256173 entity
Predicate ownedBy P347 FINISHED
Object Banedanmark E669126 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: Banedanmark | Statement: [Herning Station, ownedBy, Banedanmark]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Banedanmark
Context triple: [Herning Station, ownedBy, Banedanmark]
  • A. Banedanmark chosen
    Banedanmark is the Danish government agency responsible for owning, maintaining, and managing most of Denmark’s railway infrastructure.
  • B. Billund, Denmark
    Billund, Denmark is a small Danish town best known as the birthplace of LEGO and home to the original LEGOLAND theme park.
  • C. Denmark
    Denmark is a Nordic country in Northern Europe known for its high standard of living, strong welfare state, and role as a founding member of NATO and the United Nations.
  • D. Farum, Denmark
    Farum, Denmark is a suburban town in Furesø Municipality on the island of Zealand, known for its residential character and proximity to Copenhagen.
  • E. Karup, Denmark
    Karup, Denmark is a village in central Jutland best known as a major military hub and home to the primary air base of the Royal Danish Air Force.
  • 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_69d6aa83d1448190a66d93c32394d21f completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d75117b76c8190b0fb216b1428c3c7 completed April 9, 2026, 7:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69deb17d978c8190883b4a56e88859de completed April 14, 2026, 9:28 p.m.
Created at: April 8, 2026, 9:20 p.m.