Triple

T18797041
Position Surface form Disambiguated ID Type / Status
Subject Vendsyssel E459660 entity
Predicate hasMajorTown P316 FINISHED
Object Støvring
Støvring is a Danish town in the North Jutland region known as a local commercial and residential center.
 E1364422 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: Støvring | Statement: [Vendsyssel, hasMajorTown, Støvring]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Støvring
Context triple: [Vendsyssel, hasMajorTown, Støvring]
  • A. Solør
    Solør is a traditional district in Eastern Norway known for its rural landscapes, forestry, and agriculture.
  • B. Stavern
    Stavern is a small coastal town in southern Norway known for its historic fortress, maritime heritage, and role as a popular summer holiday destination.
  • C. Kragerø
    Kragerø is a coastal town in Norway renowned for its picturesque archipelago, historic wooden buildings, and role as a popular summer holiday destination.
  • D. Østervrå
    Østervrå is a small town in the Vendsyssel region of northern Denmark.
  • E. Søgne
    Søgne is a coastal district and former municipality in Southern Norway, now part of the city of Kristiansand in Agder county.
  • 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: Støvring
Triple: [Vendsyssel, hasMajorTown, Støvring]
Generated description
Støvring is a Danish town in the North Jutland region known as a local commercial and residential center.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Støvring
Target entity description: Støvring is a Danish town in the North Jutland region known as a local commercial and residential center.
  • A. Solør
    Solør is a traditional district in Eastern Norway known for its rural landscapes, forestry, and agriculture.
  • B. Stavern
    Stavern is a small coastal town in southern Norway known for its historic fortress, maritime heritage, and role as a popular summer holiday destination.
  • C. Kragerø
    Kragerø is a coastal town in Norway renowned for its picturesque archipelago, historic wooden buildings, and role as a popular summer holiday destination.
  • D. Østervrå chosen
    Østervrå is a small town in the Vendsyssel region of northern Denmark.
  • E. Søgne
    Søgne is a coastal district and former municipality in Southern Norway, now part of the city of Kristiansand in Agder county.
  • 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_69d8d398c7d4819091cb2f7e48948aeb completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5a020821881909749f6a1c6cd195b completed April 20, 2026, 3:40 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0705bd6a8c8190814904e816108630 completed May 15, 2026, 11:38 a.m.
NEDg Description generation batch_6a07063f12948190909bb5582b8aca5e completed May 15, 2026, 11:40 a.m.
NED2 Entity disambiguation (via description) batch_6a0706af26a8819092a88bc386af0dbe completed May 15, 2026, 11:42 a.m.
Created at: April 10, 2026, 11:53 a.m.