Triple

T23543355
Position Surface form Disambiguated ID Type / Status
Subject Randesund E577815 entity
Predicate hasNeighbourhood P4813 FINISHED
Object Søm
Søm is a residential neighborhood in Kristiansand, Norway, known for its coastal location and proximity to both urban amenities and natural areas.
 E1591472 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: Søm | Statement: [Randesund, hasNeighbourhood, Søm]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Søm
Context triple: [Randesund, hasNeighbourhood, Søm]
  • A. Sørum
    Sørum is a former municipality in Viken county, Norway, known for its rural landscapes and location in the Romerike region northeast of Oslo.
  • B. Smedvig
    Smedvig is a Norwegian family name most prominently associated with the Smedvig shipping and oil services business dynasty.
  • C. Tysvær
    Tysvær is a coastal municipality in southwestern Norway known for its fjords, islands, and location between the cities of Haugesund and Stavanger.
  • D. Svaneke
    Svaneke is a picturesque coastal town on the Danish island of Bornholm, known for its well-preserved half-timbered houses, harbor, and traditional smokehouses.
  • E. Sogn
    Sogn is a traditional district in western Norway known for its dramatic fjord landscapes, including parts of the famous Sognefjord.
  • 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: Søm
Triple: [Randesund, hasNeighbourhood, Søm]
Generated description
Søm is a residential neighborhood in Kristiansand, Norway, known for its coastal location and proximity to both urban amenities and natural areas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Søm
Target entity description: Søm is a residential neighborhood in Kristiansand, Norway, known for its coastal location and proximity to both urban amenities and natural areas.
  • A. Sørum
    Sørum is a former municipality in Viken county, Norway, known for its rural landscapes and location in the Romerike region northeast of Oslo.
  • B. Smedvig
    Smedvig is a Norwegian family name most prominently associated with the Smedvig shipping and oil services business dynasty.
  • C. Tysvær
    Tysvær is a coastal municipality in southwestern Norway known for its fjords, islands, and location between the cities of Haugesund and Stavanger.
  • D. Svaneke
    Svaneke is a picturesque coastal town on the Danish island of Bornholm, known for its well-preserved half-timbered houses, harbor, and traditional smokehouses.
  • E. Sogn
    Sogn is a traditional district in western Norway known for its dramatic fjord landscapes, including parts of the famous Sognefjord.
  • 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_69e245f9d5d08190a4a20004e1784e20 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f1ae1dbe188190bc4afe7bfa7cda0f completed April 29, 2026, 7:07 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0cdf5fc0d08190a2d4dcc0206d4315 completed May 19, 2026, 10:08 p.m.
NEDg Description generation batch_6a0ce348596481909924931969de8141 completed May 19, 2026, 10:25 p.m.
NED2 Entity disambiguation (via description) batch_6a0ce3e41c60819095760a2c5a224fb3 completed May 19, 2026, 10:27 p.m.
Created at: April 17, 2026, 6:11 p.m.