Triple

T4872368
Position Surface form Disambiguated ID Type / Status
Subject Lidingö E109113 entity
Predicate hasTwinTown P919 FINISHED
Object Søllerød
Søllerød is a locality in Rudersdal Municipality, north of Copenhagen in eastern Denmark, known for its affluent residential areas and scenic natural surroundings.
 E479211 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: Søllerød | Statement: [Lidingö, hasTwinTown, Søllerød]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Søllerød
Context triple: [Lidingö, hasTwinTown, Søllerød]
  • A. Rønne
    Rønne is the largest town and administrative center of the Danish island of Bornholm, known for its historic harbor, half-timbered houses, and Baltic Sea ferry connections.
  • B. Brønderslev
    Brønderslev is a town in northern Jutland, Denmark, known as a local commercial and administrative center surrounded by agricultural countryside.
  • C. Rødovre
    Rødovre is a suburban municipality in the Capital Region of Denmark, located just west of central Copenhagen.
  • D. Hellebæk
    Hellebæk is a coastal town in northeastern Zealand, Denmark, known for its scenic setting near Helsingør and its historic industrial and residential architecture.
  • E. Næstved
    Næstved is a historic market town and commercial center in southern Denmark, located on the island of Zealand.
  • 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: Søllerød
Triple: [Lidingö, hasTwinTown, Søllerød]
Generated description
Søllerød is a locality in Rudersdal Municipality, north of Copenhagen in eastern Denmark, known for its affluent residential areas and scenic natural surroundings.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Søllerød
Target entity description: Søllerød is a locality in Rudersdal Municipality, north of Copenhagen in eastern Denmark, known for its affluent residential areas and scenic natural surroundings.
  • A. Rønne
    Rønne is the largest town and administrative center of the Danish island of Bornholm, known for its historic harbor, half-timbered houses, and Baltic Sea ferry connections.
  • B. Brønderslev
    Brønderslev is a town in northern Jutland, Denmark, known as a local commercial and administrative center surrounded by agricultural countryside.
  • C. Rødovre
    Rødovre is a suburban municipality in the Capital Region of Denmark, located just west of central Copenhagen.
  • D. Hellebæk
    Hellebæk is a coastal town in northeastern Zealand, Denmark, known for its scenic setting near Helsingør and its historic industrial and residential architecture.
  • E. Næstved
    Næstved is a historic market town and commercial center in southern Denmark, located on the island of Zealand.
  • 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_69bd440d96a48190b0c87069adef2af1 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6d9e27908190a0c4540ee2559c4b completed March 20, 2026, 3:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69be6fb25f008190ab9b7cc904b540c9 completed March 21, 2026, 10:15 a.m.
NEDg Description generation batch_69be71ef01148190af12e1b9a2869612 completed March 21, 2026, 10:24 a.m.
NED2 Entity disambiguation (via description) batch_69be7242fc5c8190bc63ad852f937590 completed March 21, 2026, 10:26 a.m.
Created at: March 20, 2026, 1:27 p.m.