Triple

T18597556
Position Surface form Disambiguated ID Type / Status
Subject Midttrafik E454531 entity
Predicate operatesIn P82 FINISHED
Object Ikast-Brande
Ikast-Brande is a municipality in Denmark’s Central Jutland region, known for its mix of industrial activity, wind energy production, and rural communities.
E1333048 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: Ikast-Brande | Statement: [Midttrafik, operatesIn, Ikast-Brande]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ikast-Brande
Context triple: [Midttrafik, operatesIn, Ikast-Brande]
  • A. Ikast
    Ikast is a town in central Jutland, Denmark, known for its textile industry and as a local hub for sports and commerce.
  • B. Skaraborg
    Skaraborg is a historical province in southwestern Sweden known for its agricultural landscape, medieval churches, and former military significance.
  • C. Hillerød
    Hillerød is a Danish town on the island of Zealand, known for the historic Frederiksborg Castle and its role as a regional administrative and cultural center.
  • D. Ishøj
    Ishøj is a coastal town and municipality in eastern Denmark, located on the island of Zealand within the Copenhagen metropolitan area.
  • E. Fagerborg
    Fagerborg is a residential neighborhood in Oslo, Norway, known for its central location, historic buildings, and proximity to major educational institutions.
  • 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: Ikast-Brande
Triple: [Midttrafik, operatesIn, Ikast-Brande]
Generated description
Ikast-Brande is a municipality in Denmark’s Central Jutland region, known for its mix of industrial activity, wind energy production, and rural communities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ikast-Brande
Target entity description: Ikast-Brande is a municipality in Denmark’s Central Jutland region, known for its mix of industrial activity, wind energy production, and rural communities.
  • A. Ikast
    Ikast is a town in central Jutland, Denmark, known for its textile industry and as a local hub for sports and commerce.
  • B. Skaraborg
    Skaraborg is a historical province in southwestern Sweden known for its agricultural landscape, medieval churches, and former military significance.
  • C. Hillerød
    Hillerød is a Danish town on the island of Zealand, known for the historic Frederiksborg Castle and its role as a regional administrative and cultural center.
  • D. Ishøj
    Ishøj is a coastal town and municipality in eastern Denmark, located on the island of Zealand within the Copenhagen metropolitan area.
  • E. Fagerborg
    Fagerborg is a residential neighborhood in Oslo, Norway, known for its central location, historic buildings, and proximity to major educational institutions.
  • 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_69d8d38ae7e081908a98df1251842402 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5474d934481909b4afd5ef9031c73 completed April 19, 2026, 9:21 p.m.
NED1 Entity disambiguation (via context triple) batch_6a05037eda788190977fcb50aa4d2357 completed May 13, 2026, 11:04 p.m.
NEDg Description generation batch_6a0504cd76388190b67c78250297573d completed May 13, 2026, 11:10 p.m.
NED2 Entity disambiguation (via description) batch_6a0505482c588190952fe07726f64b93 completed May 13, 2026, 11:12 p.m.
Created at: April 10, 2026, 11:44 a.m.