Triple

T8002703
Position Surface form Disambiguated ID Type / Status
Subject Bærum E186288 entity
Predicate hasSettlement P1068 FINISHED
Object Høvik
Høvik is a suburban residential area and neighborhood in the municipality of Bærum in Viken county, Norway.
 E714927 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: Høvik | Statement: [Bærum, hasSettlement, Høvik]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Høvik
Context triple: [Bærum, hasSettlement, Høvik]
  • A. Håvik
    Håvik is a small coastal village located in Karmøy municipality in Rogaland county, southwestern Norway.
  • B. Bærum
    Bærum is a wealthy suburban municipality just west of Oslo, Norway, known for its high standard of living and residential communities.
  • C. Ullensaker
    Ullensaker is a municipality in Viken county, Norway, best known for hosting Oslo Airport, Gardermoen, the country’s main international airport.
  • D. Sokna
    Sokna is an extinct Eastern Berber language formerly spoken around the oasis town of Sokna in central Libya.
  • E. Torshov
    Torshov is a residential neighborhood in Oslo, Norway, known for its early 20th-century architecture, green spaces, and vibrant local culture.
  • 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: Høvik
Triple: [Bærum, hasSettlement, Høvik]
Generated description
Høvik is a suburban residential area and neighborhood in the municipality of Bærum in Viken county, Norway.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Høvik
Target entity description: Høvik is a suburban residential area and neighborhood in the municipality of Bærum in Viken county, Norway.
  • A. Håvik
    Håvik is a small coastal village located in Karmøy municipality in Rogaland county, southwestern Norway.
  • B. Bærum
    Bærum is a wealthy suburban municipality just west of Oslo, Norway, known for its high standard of living and residential communities.
  • C. Ullensaker
    Ullensaker is a municipality in Viken county, Norway, best known for hosting Oslo Airport, Gardermoen, the country’s main international airport.
  • D. Sokna
    Sokna is an extinct Eastern Berber language formerly spoken around the oasis town of Sokna in central Libya.
  • E. Torshov
    Torshov is a residential neighborhood in Oslo, Norway, known for its early 20th-century architecture, green spaces, and vibrant local culture.
  • 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_69ca82aaaf24819084b94d18f699ba53 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3cf2918081909ee0afab11caed63 completed March 31, 2026, 3:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69ccbe26a07c8190af48bb9189b12a44 completed April 1, 2026, 6:41 a.m.
NEDg Description generation batch_69ccc24a39f88190995f076d1a7ec3e7 completed April 1, 2026, 6:59 a.m.
NED2 Entity disambiguation (via description) batch_69ccc37f0ca88190b4e077f23dbbe6f8 completed April 1, 2026, 7:04 a.m.
Created at: March 30, 2026, 5:18 p.m.