Triple

T8309989
Position Surface form Disambiguated ID Type / Status
Subject Region of Southern Denmark E194566 entity
Predicate containsCity P294 FINISHED
Object Billund
Billund is a Danish town best known as the birthplace of LEGO and home to the original LEGOLAND theme park.
E725078 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: Billund | Statement: [Region of Southern Denmark, containsCity, Billund]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Billund
Context triple: [Region of Southern Denmark, containsCity, Billund]
  • A. Hellebæk
    Hellebæk is a coastal town in northeastern Zealand, Denmark, known for its scenic setting near Helsingør and its historic industrial and residential architecture.
  • B. Padborg
    Padborg is a Danish town in Southern Jutland known as an important transport and border crossing hub between Denmark and Germany.
  • C. Skanderborg
    Skanderborg is a Danish town in Jutland known for its lakeside setting and annual music festival, Smukfest.
  • D. Thisted
    Thisted is a coastal town and municipality in northwestern Jutland, Denmark, known for its scenic location by the Limfjord and its role as a regional commercial and cultural center.
  • E. Haderslev
    Haderslev is a historic town in southern Denmark known for its medieval cathedral, old town center, and role as a regional cultural and administrative hub.
  • 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: Billund
Triple: [Region of Southern Denmark, containsCity, Billund]
Generated description
Billund is a Danish town best known as the birthplace of LEGO and home to the original LEGOLAND theme park.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Billund
Target entity description: Billund is a Danish town best known as the birthplace of LEGO and home to the original LEGOLAND theme park.
  • A. Hellebæk
    Hellebæk is a coastal town in northeastern Zealand, Denmark, known for its scenic setting near Helsingør and its historic industrial and residential architecture.
  • B. Padborg
    Padborg is a Danish town in Southern Jutland known as an important transport and border crossing hub between Denmark and Germany.
  • C. Skanderborg
    Skanderborg is a Danish town in Jutland known for its lakeside setting and annual music festival, Smukfest.
  • D. Thisted
    Thisted is a coastal town and municipality in northwestern Jutland, Denmark, known for its scenic location by the Limfjord and its role as a regional commercial and cultural center.
  • E. Haderslev
    Haderslev is a historic town in southern Denmark known for its medieval cathedral, old town center, and role as a regional cultural and administrative hub.
  • F. None of above. chosen

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_69ca82e613e88190bf8139669bbd0d53 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7f2d2c30819095075940479b75a7 completed March 31, 2026, 8 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd95665390819089c8becad018cf51 completed April 1, 2026, 10 p.m.
NEDg Description generation batch_69cda62070888190b55b3f54d29e28e7 completed April 1, 2026, 11:11 p.m.
NED2 Entity disambiguation (via description) batch_69cdb21a65d88190a19dd41f95d173c8 completed April 2, 2026, 12:02 a.m.
Created at: March 30, 2026, 5:54 p.m.