Triple

T10852232
Position Surface form Disambiguated ID Type / Status
Subject Herning Station E256173 entity
Predicate connectsTo P845 FINISHED
Object Struer E669133 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: Struer | Statement: [Herning Station, connectsTo, Struer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Struer
Context triple: [Herning Station, connectsTo, Struer]
  • A. Struer chosen
    Struer is a Danish town in the Central Denmark Region known for its location on the Limfjord and as the historic home of the audio company Bang & Olufsen.
  • B. Magura
    Magura is a town and district headquarters in southwestern Bangladesh known for its agricultural surroundings and location within the Khulna Division.
  • C. Skeid
    Skeid is a Norwegian sports club best known for its football team and local rivalry with Lyn in Oslo.
  • D. Leister
    Leister is a surname of English origin borne by various individuals, including those with the given name Edward.
  • E. Steeg
    Steeg is a small alpine village in the Austrian state of Tyrol, known for its scenic location in the upper Lech Valley near the Arlberg region.
  • 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.