Triple

T7180095
Position Surface form Disambiguated ID Type / Status
Subject Hellebæk E167423 entity
Predicate hasNearbyLocality P3883 FINISHED
Object Ålsgårde
Ålsgårde is a coastal town in North Zealand, Denmark, known for its residential areas and proximity to the Øresund Strait.
 E647875 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: Ålsgårde | Statement: [Hellebæk, hasNearbyLocality, Ålsgårde]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ålsgårde
Context triple: [Hellebæk, hasNearbyLocality, Ålsgårde]
  • A. Lodalen
    Lodalen is a small valley and residential-industrial area in Oslo, Norway, situated near the inner-city districts and railway facilities.
  • B. Ulriksdal
    Ulriksdal is a district in Solna, Sweden, known for the historic Ulriksdal Palace and its surrounding parklands along the Edsviken inlet.
  • C. Norsborg
    Norsborg is a suburban district in Botkyrka Municipality, southwest of central Stockholm, Sweden, known as the terminus area of the Stockholm metro’s red line.
  • D. Fagerborg
    Fagerborg is a residential neighborhood in Oslo, Norway, known for its central location, historic buildings, and proximity to major educational institutions.
  • E. Aulestad
    Aulestad is the historic Norwegian country estate and museum best known as the longtime home of Nobel Prize–winning writer Bjørnstjerne Bjørnson.
  • 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: Ålsgårde
Triple: [Hellebæk, hasNearbyLocality, Ålsgårde]
Generated description
Ålsgårde is a coastal town in North Zealand, Denmark, known for its residential areas and proximity to the Øresund Strait.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ålsgårde
Target entity description: Ålsgårde is a coastal town in North Zealand, Denmark, known for its residential areas and proximity to the Øresund Strait.
  • A. Lodalen
    Lodalen is a small valley and residential-industrial area in Oslo, Norway, situated near the inner-city districts and railway facilities.
  • B. Ulriksdal
    Ulriksdal is a district in Solna, Sweden, known for the historic Ulriksdal Palace and its surrounding parklands along the Edsviken inlet.
  • C. Norsborg
    Norsborg is a suburban district in Botkyrka Municipality, southwest of central Stockholm, Sweden, known as the terminus area of the Stockholm metro’s red line.
  • D. Fagerborg
    Fagerborg is a residential neighborhood in Oslo, Norway, known for its central location, historic buildings, and proximity to major educational institutions.
  • E. Aulestad
    Aulestad is the historic Norwegian country estate and museum best known as the longtime home of Nobel Prize–winning writer Bjørnstjerne Bjørnson.
  • 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_69c6888a7c548190a3d39b52a393080f completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e8ba91908190a9055d4e026b655c completed March 27, 2026, 8:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7b935eb088190acb0b8a6b75addbb completed March 28, 2026, 11:19 a.m.
NEDg Description generation batch_69c7bcfaf8608190908c5b58ecdf9aff completed March 28, 2026, 11:35 a.m.
NED2 Entity disambiguation (via description) batch_69c7bd68f4688190aa8ac988d2435bb7 completed March 28, 2026, 11:37 a.m.
Created at: March 27, 2026, 2:49 p.m.