Triple

T6592408
Position Surface form Disambiguated ID Type / Status
Subject Sinsen E148392 entity
Predicate hasNearbyNeighborhood P350 FINISHED
Object Løren
Løren is a rapidly developing residential and commercial neighborhood in Oslo, Norway, known for its modern housing, new infrastructure, and proximity to central city areas.
 E599687 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: Løren | Statement: [Sinsen, hasNearbyNeighborhood, Løren]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Løren
Context triple: [Sinsen, hasNearbyNeighborhood, Løren]
  • A. Lofthus
    Lofthus is a village in Norway’s Hardanger region, known for its fruit orchards, fjord scenery, and role as a gateway to hiking routes like the Hardangervidda plateau.
  • B. Lodalen
    Lodalen is a small valley and residential-industrial area in Oslo, Norway, situated near the inner-city districts and railway facilities.
  • C. Lofsrud
    Lofsrud is a residential area and neighborhood within the Søndre Nordstrand borough of Oslo, Norway.
  • D. Trondenes
    Trondenes is a historic former municipality and parish in northern Norway, known for its medieval stone church and role as an administrative center in the Harstad region.
  • E. Holtålen
    Holtålen is a rural municipality in Trøndelag county, Norway, known for its valleys, rivers, and traditional farming and forestry.
  • 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: Løren
Triple: [Sinsen, hasNearbyNeighborhood, Løren]
Generated description
Løren is a rapidly developing residential and commercial neighborhood in Oslo, Norway, known for its modern housing, new infrastructure, and proximity to central city areas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Løren
Target entity description: Løren is a rapidly developing residential and commercial neighborhood in Oslo, Norway, known for its modern housing, new infrastructure, and proximity to central city areas.
  • A. Lofthus
    Lofthus is a village in Norway’s Hardanger region, known for its fruit orchards, fjord scenery, and role as a gateway to hiking routes like the Hardangervidda plateau.
  • B. Lodalen
    Lodalen is a small valley and residential-industrial area in Oslo, Norway, situated near the inner-city districts and railway facilities.
  • C. Lofsrud
    Lofsrud is a residential area and neighborhood within the Søndre Nordstrand borough of Oslo, Norway.
  • D. Trondenes
    Trondenes is a historic former municipality and parish in northern Norway, known for its medieval stone church and role as an administrative center in the Harstad region.
  • E. Holtålen
    Holtålen is a rural municipality in Trøndelag county, Norway, known for its valleys, rivers, and traditional farming and forestry.
  • 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_69c687e7b8688190811ffee72e096468 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6aece1f848190a11676e072afb002 completed March 27, 2026, 4:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6cbba656c81909c3876a8f2f7300e completed March 27, 2026, 6:26 p.m.
NEDg Description generation batch_69c6cd08a9c88190a481d4d3f8e680bf completed March 27, 2026, 6:31 p.m.
NED2 Entity disambiguation (via description) batch_69c6cdc859cc8190bbae2efc39409021 completed March 27, 2026, 6:34 p.m.
Created at: March 27, 2026, 1:55 p.m.