Triple

T6304152
Position Surface form Disambiguated ID Type / Status
Subject Vestre Aker E141330 entity
Predicate contains P35 FINISHED
Object Smestad
Smestad is a residential neighborhood in Oslo, Norway, known for its affluent housing and proximity to green areas and good public transport.
 E673445 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: Smestad | Statement: [Vestre Aker, contains, Smestad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Smestad
Context triple: [Vestre Aker, contains, Smestad]
  • A. Slemdal
    Slemdal is a residential neighborhood in the Vestre Aker borough of Oslo, Norway, known for its green surroundings and affluent character.
  • B. Drammen
    Drammen is a city and municipality in southeastern Norway known for its riverside setting along the Drammenselva and its role as a regional commercial and transport hub.
  • C. Lørenskog
    Lørenskog is a suburban municipality in Viken county, Norway, located just east of Oslo and known for its residential areas and commercial centers.
  • D. Sandnes
    Sandnes is a city in southwestern Norway, near Stavanger, known for its proximity to fjords and outdoor recreation areas.
  • E. Tvedestrand
    Tvedestrand is a coastal town and municipality in southern Norway known for its wooden houses, maritime heritage, and picturesque archipelago.
  • 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: Smestad
Triple: [Vestre Aker, contains, Smestad]
Generated description
Smestad is a residential neighborhood in Oslo, Norway, known for its affluent housing and proximity to green areas and good public transport.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Smestad
Target entity description: Smestad is a residential neighborhood in Oslo, Norway, known for its affluent housing and proximity to green areas and good public transport.
  • A. Slemdal
    Slemdal is a residential neighborhood in the Vestre Aker borough of Oslo, Norway, known for its green surroundings and affluent character.
  • B. Drammen
    Drammen is a city and municipality in southeastern Norway known for its riverside setting along the Drammenselva and its role as a regional commercial and transport hub.
  • C. Lørenskog
    Lørenskog is a suburban municipality in Viken county, Norway, located just east of Oslo and known for its residential areas and commercial centers.
  • D. Sandnes
    Sandnes is a city in southwestern Norway, near Stavanger, known for its proximity to fjords and outdoor recreation areas.
  • E. Tvedestrand
    Tvedestrand is a coastal town and municipality in southern Norway known for its wooden houses, maritime heritage, and picturesque archipelago.
  • 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_69c008cf0ad4819095def81e2bd42f9f completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0645f26a881909d5746151c0843cc completed March 22, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69c85695cc608190aa6ed016bd3f8929 completed March 28, 2026, 10:30 p.m.
NEDg Description generation batch_69c85765d1f48190b171ff87a15c5b74 completed March 28, 2026, 10:34 p.m.
NED2 Entity disambiguation (via description) batch_69c8580963748190b81bd7437259da28 completed March 28, 2026, 10:36 p.m.
Created at: March 22, 2026, 4:28 p.m.