Triple

T5729581
Position Surface form Disambiguated ID Type / Status
Subject Frogner E126347 entity
Predicate contains P35 FINISHED
Object Skillebekk
Skillebekk is a residential neighborhood in Oslo, Norway, known for its central location, historic architecture, and proximity to the Frogner and city center areas.
 E540479 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: Skillebekk | Statement: [Frogner, contains, Skillebekk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Skillebekk
Context triple: [Frogner, contains, Skillebekk]
  • A. Bekkestua
    Bekkestua is a suburban center in Bærum, Norway, functioning as a local commercial and transport hub just west of Oslo.
  • B. Brattvåg
    Brattvåg is a small coastal village in western Norway known for its maritime industry and scenic fjord landscape.
  • C. Evenskjer
    Evenskjer is a small village in Northern Norway that serves as an administrative and service center in the Troms region.
  • D. Stabekk
    Stabekk is a suburban area in Bærum, Norway, known for its residential neighborhoods, proximity to Oslo, and good transport connections.
  • E. Gloppen
    Gloppen is a municipality in Vestland county, Norway, known for its fjord landscapes, agriculture, and the village of Sandane as its administrative center.
  • 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: Skillebekk
Triple: [Frogner, contains, Skillebekk]
Generated description
Skillebekk is a residential neighborhood in Oslo, Norway, known for its central location, historic architecture, and proximity to the Frogner and city center areas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Skillebekk
Target entity description: Skillebekk is a residential neighborhood in Oslo, Norway, known for its central location, historic architecture, and proximity to the Frogner and city center areas.
  • A. Bekkestua
    Bekkestua is a suburban center in Bærum, Norway, functioning as a local commercial and transport hub just west of Oslo.
  • B. Brattvåg
    Brattvåg is a small coastal village in western Norway known for its maritime industry and scenic fjord landscape.
  • C. Evenskjer
    Evenskjer is a small village in Northern Norway that serves as an administrative and service center in the Troms region.
  • D. Stabekk
    Stabekk is a suburban area in Bærum, Norway, known for its residential neighborhoods, proximity to Oslo, and good transport connections.
  • E. Gloppen
    Gloppen is a municipality in Vestland county, Norway, known for its fjord landscapes, agriculture, and the village of Sandane as its administrative center.
  • 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_69c025303860819093e51f176babed71 completed March 22, 2026, 5:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69c05a8cca748190b471c842fd2ce218 completed March 22, 2026, 9:09 p.m.
NEDg Description generation batch_69c05b7c3bd48190ad8303bf1bb3ec6a completed March 22, 2026, 9:13 p.m.
NED2 Entity disambiguation (via description) batch_69c05c22c31081909a9a67d99e7c728c completed March 22, 2026, 9:16 p.m.
Created at: March 22, 2026, 3:47 p.m.