Triple

T7591473
Position Surface form Disambiguated ID Type / Status
Subject Great Belt Bridge E179744 entity
Predicate startPoint P389 FINISHED
Object Halsskov
Halsskov is a district and ferry port in the Danish town of Korsør on the island of Zealand, known as the western landfall of the Great Belt Bridge.
 E675344 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: Halsskov | Statement: [Great Belt Bridge, startPoint, Halsskov]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Halsskov
Context triple: [Great Belt Bridge, startPoint, Halsskov]
  • 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. Blangsted
    Blangsted is a surname most notably associated with Folmar Blangsted, a film editor.
  • C. Vadsø
    Vadsø is a small coastal town and administrative center in Finnmark, known for its Arctic location on the Varanger Peninsula and its role as a hub of Sami and Kven culture in Northern Norway.
  • D. Vækerø
    Vækerø is a residential and commercial area in Oslo, Norway, located along the western waterfront and known for its mix of housing, offices, and green spaces.
  • E. Norderhov
    Norderhov is a village in the municipality of Ringerike in Buskerud, Norway, known for its historic church and rural surroundings.
  • 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: Halsskov
Triple: [Great Belt Bridge, startPoint, Halsskov]
Generated description
Halsskov is a district and ferry port in the Danish town of Korsør on the island of Zealand, known as the western landfall of the Great Belt Bridge.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Halsskov
Target entity description: Halsskov is a district and ferry port in the Danish town of Korsør on the island of Zealand, known as the western landfall of the Great Belt Bridge.
  • 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. Blangsted
    Blangsted is a surname most notably associated with Folmar Blangsted, a film editor.
  • C. Vadsø
    Vadsø is a small coastal town and administrative center in Finnmark, known for its Arctic location on the Varanger Peninsula and its role as a hub of Sami and Kven culture in Northern Norway.
  • D. Vækerø
    Vækerø is a residential and commercial area in Oslo, Norway, located along the western waterfront and known for its mix of housing, offices, and green spaces.
  • E. Norderhov
    Norderhov is a village in the municipality of Ringerike in Buskerud, Norway, known for its historic church and rural surroundings.
  • 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_69c69f335248819093c1006f30513708 completed March 27, 2026, 3:16 p.m.
NER Named-entity recognition batch_69c6f9b746ac8190b255afdfb9635f72 completed March 27, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69c86192b5d88190b0a02cf303462bfb completed March 28, 2026, 11:17 p.m.
NEDg Description generation batch_69c8628d252c8190bc67e90f497f1ada completed March 28, 2026, 11:21 p.m.
NED2 Entity disambiguation (via description) batch_69c8631e5c2c8190b1c593ca9bbf039c completed March 28, 2026, 11:24 p.m.
Created at: March 27, 2026, 3:53 p.m.