Triple

T7488500
Position Surface form Disambiguated ID Type / Status
Subject East Jutland E176943 entity
Predicate contains P35 FINISHED
Object Silkeborg
Silkeborg is a Danish town in central Jutland known for its surrounding lake district, forests, and outdoor recreation.
 E615916 NE FINISHED

How this triple was built (4 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: [East Jutland, contains, Silkeborg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Silkeborg
Context triple: [East Jutland, contains, Silkeborg]
  • A. Holstebro
    Holstebro is a town in western Jutland, Denmark, known as a regional center that hosts significant Danish Army military facilities.
  • B. 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.
  • C. 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.
  • D. Slagelse
    Slagelse is a town on the island of Zealand in Denmark known for its military presence, historical significance, and role as a regional commercial center.
  • E. Skanderborg
    Skanderborg is a Danish town in Jutland known for its lakeside setting and annual music festival, Smukfest.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Silkeborg
Triple: [East Jutland, contains, Silkeborg]
Generated description
Silkeborg is a Danish town in central Jutland known for its surrounding lake district, forests, and outdoor recreation.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Silkeborg
Target entity description: Silkeborg is a Danish town in central Jutland known for its surrounding lake district, forests, and outdoor recreation.
  • A. Holstebro
    Holstebro is a town in western Jutland, Denmark, known as a regional center that hosts significant Danish Army military facilities.
  • B. 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.
  • C. 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.
  • D. Slagelse
    Slagelse is a town on the island of Zealand in Denmark known for its military presence, historical significance, and role as a regional commercial center.
  • E. Skanderborg chosen
    Skanderborg is a Danish town in Jutland known for its lakeside setting and annual music festival, Smukfest.
  • F. None of above.

Provenance (5 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_69c69f24ac508190bb98fe927c0bd065 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f55965ac81909d3c3a5422b22d44 completed March 27, 2026, 9:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8b4e9b3348190a24823ff9ad3431e completed March 29, 2026, 5:13 a.m.
NEDg Description generation batch_69c8b79db9a08190ab7014085c6d2fb4 completed March 29, 2026, 5:24 a.m.
NED2 Entity disambiguation (via description) batch_69c8b7e980d08190ad1547e3147d36c6 completed March 29, 2026, 5:26 a.m.
Created at: March 27, 2026, 3:43 p.m.