Triple

T19003364
Position Surface form Disambiguated ID Type / Status
Subject Central Jutland E465011 entity
Predicate hasMajorCity P316 FINISHED
Object Silkeborg 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: Silkeborg | Statement: [Central Jutland, hasMajorCity, Silkeborg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Silkeborg
Context triple: [Central Jutland, hasMajorCity, Silkeborg]
  • A. Silkeborg chosen
    Silkeborg is a Danish town in central Jutland known for its surrounding lake district, forests, and outdoor recreation.
  • B. Holstebro
    Holstebro is a town in western Jutland, Denmark, known as a regional center that hosts significant Danish Army military facilities.
  • C. Sønderborg
    Sønderborg is a coastal town in southern Denmark known for its historic castle, waterfront setting on the island of Als, and role as a regional cultural and educational center.
  • D. 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.
  • E. Skjern
    Skjern is a town in western Jutland, Denmark, known for its location near the Skjern River and its surrounding agricultural landscape.
  • 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_69d8dd01a56c81909694a128c66b21d7 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5d6a252588190a40398b1879fb096 completed April 20, 2026, 7:32 a.m.
Created at: April 10, 2026, 12:01 p.m.