Triple

T18927139
Position Surface form Disambiguated ID Type / Status
Subject Guldborgsund Municipality E463002 entity
Predicate containsSettlement P847 FINISHED
Object Nysted
Nysted is a small coastal town in southeastern Denmark known for its historic harbor, medieval church, and proximity to the Baltic Sea.
 E1426953 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: Nysted | Statement: [Guldborgsund Municipality, containsSettlement, Nysted]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nysted
Context triple: [Guldborgsund Municipality, containsSettlement, Nysted]
  • A. Farsø
    Farsø is a small Danish town in North Jutland, best known as the birthplace of Nobel Prize–winning author Johannes V. Jensen.
  • B. Oksbøl
    Oksbøl is a town in southwestern Jutland, Denmark, known for its military training areas and historical role as a garrison location.
  • C. Græsted
    Græsted is a small town in North Zealand, Denmark, known for its rural character and location along the Gribskov railway line.
  • D. Sundbyøster
    Sundbyøster is a district of Copenhagen located on the island of Amager, known primarily as a residential urban area.
  • E. Skælskør
    Skælskør is a small coastal town in western Zealand, Denmark, known for its historic harbor, scenic fjord, and traditional Danish architecture.
  • 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: Nysted
Triple: [Guldborgsund Municipality, containsSettlement, Nysted]
Generated description
Nysted is a small coastal town in southeastern Denmark known for its historic harbor, medieval church, and proximity to the Baltic Sea.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nysted
Target entity description: Nysted is a small coastal town in southeastern Denmark known for its historic harbor, medieval church, and proximity to the Baltic Sea.
  • A. Farsø
    Farsø is a small Danish town in North Jutland, best known as the birthplace of Nobel Prize–winning author Johannes V. Jensen.
  • B. Oksbøl
    Oksbøl is a town in southwestern Jutland, Denmark, known for its military training areas and historical role as a garrison location.
  • C. Græsted
    Græsted is a small town in North Zealand, Denmark, known for its rural character and location along the Gribskov railway line.
  • D. Sundbyøster
    Sundbyøster is a district of Copenhagen located on the island of Amager, known primarily as a residential urban area.
  • E. Skælskør
    Skælskør is a small coastal town in western Zealand, Denmark, known for its historic harbor, scenic fjord, and traditional Danish architecture.
  • 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_69d8dcfdbbb881909964fa5a75bd0b48 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5c9bc36588190ae9cc3b8abf8afd4 completed April 20, 2026, 6:37 a.m.
NED1 Entity disambiguation (via context triple) batch_6a087067f6988190bbda7f2a4b1bde28 completed May 16, 2026, 1:26 p.m.
NEDg Description generation batch_6a0871146b248190ac91cf010a984e1f completed May 16, 2026, 1:28 p.m.
NED2 Entity disambiguation (via description) batch_6a0871a818688190ad69bcf84e33d014 completed May 16, 2026, 1:31 p.m.
Created at: April 10, 2026, 11:59 a.m.