Triple

T7853802
Position Surface form Disambiguated ID Type / Status
Subject Skedsmo E182120 entity
Predicate borderedBy P224 FINISHED
Object Rælingen
Rælingen is a municipality in Viken county, Norway, known for its proximity to Oslo and its mix of residential areas, forests, and lakes.
 E695708 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: Rælingen | Statement: [Skedsmo, borderedBy, Rælingen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Rælingen
Context triple: [Skedsmo, borderedBy, Rælingen]
  • A. Tysvær
    Tysvær is a coastal municipality in southwestern Norway known for its fjords, islands, and location between the cities of Haugesund and Stavanger.
  • B. 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.
  • C. Kvænangen
    Kvænangen is a fjord in northern Norway known for its dramatic coastal scenery, rich marine life, and traditional fishing communities.
  • D. Dælenenga
    Dælenenga is an area in Oslo, Norway, known for its sports facilities and urban character within the inner-city district.
  • E. Rönninge
    Rönninge is a locality in Stockholm County, Sweden, serving as the central town of Salem Municipality.
  • 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: Rælingen
Triple: [Skedsmo, borderedBy, Rælingen]
Generated description
Rælingen is a municipality in Viken county, Norway, known for its proximity to Oslo and its mix of residential areas, forests, and lakes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Rælingen
Target entity description: Rælingen is a municipality in Viken county, Norway, known for its proximity to Oslo and its mix of residential areas, forests, and lakes.
  • A. Tysvær
    Tysvær is a coastal municipality in southwestern Norway known for its fjords, islands, and location between the cities of Haugesund and Stavanger.
  • B. 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.
  • C. Kvænangen
    Kvænangen is a fjord in northern Norway known for its dramatic coastal scenery, rich marine life, and traditional fishing communities.
  • D. Dælenenga
    Dælenenga is an area in Oslo, Norway, known for its sports facilities and urban character within the inner-city district.
  • E. Rönninge
    Rönninge is a locality in Stockholm County, Sweden, serving as the central town of Salem Municipality.
  • 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_69ca82869ee08190b8f9040dbc2c0467 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb18ed56d481909266d862e0ae152d completed March 31, 2026, 12:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5b1e9e808190a0eb2dea5288e743 completed March 31, 2026, 5:26 a.m.
NEDg Description generation batch_69cb5def38e88190864d84abd7959aa3 completed March 31, 2026, 5:38 a.m.
NED2 Entity disambiguation (via description) batch_69cb767b198481909cfc1f7a44e6f0d8 completed March 31, 2026, 7:23 a.m.
Created at: March 30, 2026, 4:51 p.m.