Triple

T7758657
Position Surface form Disambiguated ID Type / Status
Subject Slotsholmen E175961 entity
Predicate crossedBy P416 FINISHED
Object Højbro
Højbro is a historic bridge in central Copenhagen that connects the islet of Slotsholmen with the rest of the city across the Inner Harbour.
E686970 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: Højbro | Statement: [Slotsholmen, crossedBy, Højbro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Højbro
Context triple: [Slotsholmen, crossedBy, Højbro]
  • A. Hellebæk
    Hellebæk is a coastal town in northeastern Zealand, Denmark, known for its scenic setting near Helsingør and its historic industrial and residential architecture.
  • B. Bragernes
    Bragernes is a historic former town and district that now forms the northern part of the city of Drammen in Norway.
  • C. Brønderslev
    Brønderslev is a town in northern Jutland, Denmark, known as a local commercial and administrative center surrounded by agricultural countryside.
  • D. Knudshoved
    Knudshoved is a coastal area on the Danish island of Funen that serves as a key transport hub and former ferry terminal at the western end of the Great Belt crossing.
  • E. Møllehøj
    Møllehøj is the highest natural point in Denmark, located in the hilly region of eastern Jutland.
  • 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: Højbro
Triple: [Slotsholmen, crossedBy, Højbro]
Generated description
Højbro is a historic bridge in central Copenhagen that connects the islet of Slotsholmen with the rest of the city across the Inner Harbour.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Højbro
Target entity description: Højbro is a historic bridge in central Copenhagen that connects the islet of Slotsholmen with the rest of the city across the Inner Harbour.
  • A. Hellebæk
    Hellebæk is a coastal town in northeastern Zealand, Denmark, known for its scenic setting near Helsingør and its historic industrial and residential architecture.
  • B. Bragernes
    Bragernes is a historic former town and district that now forms the northern part of the city of Drammen in Norway.
  • C. Brønderslev
    Brønderslev is a town in northern Jutland, Denmark, known as a local commercial and administrative center surrounded by agricultural countryside.
  • D. Knudshoved
    Knudshoved is a coastal area on the Danish island of Funen that serves as a key transport hub and former ferry terminal at the western end of the Great Belt crossing.
  • E. Møllehøj
    Møllehøj is the highest natural point in Denmark, located in the hilly region of eastern Jutland.
  • 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_69c6996180088190832e38e8d83ff54a completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c703de43d08190ac28bc17cd3e5ffa completed March 27, 2026, 10:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8c7cf538c8190aa86c27fff42efb0 completed March 29, 2026, 6:33 a.m.
NEDg Description generation batch_69c8c8a18860819081a88f80544db83d completed March 29, 2026, 6:37 a.m.
NED2 Entity disambiguation (via description) batch_69c8c900a28c819097449e8ceb373718 completed March 29, 2026, 6:38 a.m.
Created at: March 27, 2026, 4:09 p.m.