Triple

T5727550
Position Surface form Disambiguated ID Type / Status
Subject Folmar Blangsted E126301 entity
Predicate familyName P18 FINISHED
Object Blangsted
Blangsted is a surname most notably associated with Folmar Blangsted, a film editor.
E545562 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: Blangsted | Statement: [Folmar Blangsted, familyName, Blangsted]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Blangsted
Context triple: [Folmar Blangsted, familyName, Blangsted]
  • 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. Ginnerup
    Ginnerup is a small village in Denmark best known as the birthplace of former Danish Prime Minister and NATO Secretary General Anders Fogh Rasmussen.
  • C. Bragernes
    Bragernes is a historic former town and district that now forms the northern part of the city of Drammen in Norway.
  • D. Norderhov
    Norderhov is a village in the municipality of Ringerike in Buskerud, Norway, known for its historic church and rural surroundings.
  • 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: Blangsted
Triple: [Folmar Blangsted, familyName, Blangsted]
Generated description
Blangsted is a surname most notably associated with Folmar Blangsted, a film editor.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Blangsted
Target entity description: Blangsted is a surname most notably associated with Folmar Blangsted, a film editor.
  • 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. Ginnerup
    Ginnerup is a small village in Denmark best known as the birthplace of former Danish Prime Minister and NATO Secretary General Anders Fogh Rasmussen.
  • C. Bragernes
    Bragernes is a historic former town and district that now forms the northern part of the city of Drammen in Norway.
  • D. Norderhov
    Norderhov is a village in the municipality of Ringerike in Buskerud, Norway, known for its historic church and rural surroundings.
  • 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_69c0082f723881908ce8bb13a0c0f8b7 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0250c0ca081909340abae204cc226 completed March 22, 2026, 5:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69c07dffe45481909eb617e40c83bd14 completed March 22, 2026, 11:40 p.m.
NEDg Description generation batch_69c08e19e7a481909a75c883bead8a35 completed March 23, 2026, 12:49 a.m.
NED2 Entity disambiguation (via description) batch_69c08e8f59548190a0f938a259e48212 completed March 23, 2026, 12:51 a.m.
Created at: March 22, 2026, 3:47 p.m.