Triple

T5098093
Position Surface form Disambiguated ID Type / Status
Subject Møre og Romsdal E114915 entity
Predicate containsSettlement P847 FINISHED
Object Smøla
Smøla is a coastal municipality and island in western Norway known for its flat, windswept landscape, fishing communities, and large wind farm.
 E524377 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: Smøla | Statement: [Møre og Romsdal, containsSettlement, Smøla]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Smøla
Context triple: [Møre og Romsdal, containsSettlement, Smøla]
  • A. Rolvsøy
    Rolvsøy is a district and former municipality that now forms part of the city of Fredrikstad in Viken county, Norway.
  • B. Vegårshei
    Vegårshei is a rural municipality in Agder county in southern Norway, known for its forests, lakes, and traditional inland communities.
  • C. Sørkjosen
    Sørkjosen is a small coastal village in Northern Norway known as a gateway to the Reisa valley and Reisa National Park.
  • D. Mortensrud
    Mortensrud is a residential neighborhood in the Søndre Nordstrand borough of Oslo, Norway, known for its multicultural population and modern church, and served as the terminus of an Oslo Metro line.
  • E. Malmøya
    Malmøya is a notable island in the Oslofjord known for its natural landscapes and recreational areas near Oslo, Norway.
  • 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: Smøla
Triple: [Møre og Romsdal, containsSettlement, Smøla]
Generated description
Smøla is a coastal municipality and island in western Norway known for its flat, windswept landscape, fishing communities, and large wind farm.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Smøla
Target entity description: Smøla is a coastal municipality and island in western Norway known for its flat, windswept landscape, fishing communities, and large wind farm.
  • A. Rolvsøy
    Rolvsøy is a district and former municipality that now forms part of the city of Fredrikstad in Viken county, Norway.
  • B. Vegårshei
    Vegårshei is a rural municipality in Agder county in southern Norway, known for its forests, lakes, and traditional inland communities.
  • C. Sørkjosen
    Sørkjosen is a small coastal village in Northern Norway known as a gateway to the Reisa valley and Reisa National Park.
  • D. Mortensrud
    Mortensrud is a residential neighborhood in the Søndre Nordstrand borough of Oslo, Norway, known for its multicultural population and modern church, and served as the terminus of an Oslo Metro line.
  • E. Malmøya
    Malmøya is a notable island in the Oslofjord known for its natural landscapes and recreational areas near Oslo, Norway.
  • 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_69bd443fc49c819089629c00e311310c completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd7567d21081909227ed8f08b74c71 completed March 20, 2026, 4:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf70c59678819097aed5af25f36b66 completed March 22, 2026, 4:32 a.m.
NEDg Description generation batch_69bf721b227081909d3d87917b13ec5c completed March 22, 2026, 4:37 a.m.
NED2 Entity disambiguation (via description) batch_69bf7262f3688190a25efd5c6b480488 completed March 22, 2026, 4:38 a.m.
Created at: March 20, 2026, 1:40 p.m.