Triple

T16137446
Position Surface form Disambiguated ID Type / Status
Subject Askøy Municipality E391567 entity
Predicate hasIsland P970 FINISHED
Object Hanøy
Hanøy is a small Norwegian island that forms part of Askøy Municipality in Vestland county.
 E1334635 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: Hanøy | Statement: [Askøy Municipality, hasIsland, Hanøy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hanøy
Context triple: [Askøy Municipality, hasIsland, Hanøy]
  • A. Florø
    Florø is a coastal town in western Norway known as the country’s westernmost town and a traditional center for fishing and maritime industries.
  • B. Ålesund
    Ålesund is a coastal Norwegian city renowned for its distinctive Art Nouveau architecture and location across several islands in Western Norway.
  • C. Bodø
    Bodø is a coastal city in northern Norway known as a regional hub for culture, transport, and access to Arctic nature.
  • D. Tromsø
    Tromsø is a city in northern Norway known for its Arctic location, vibrant cultural scene, and prominence as a viewing spot for the Northern Lights.
  • E. Stavanger
    Stavanger is a coastal city in southwestern Norway known for its oil industry hub status, historic wooden houses, and proximity to natural attractions like the Lysefjord and Preikestolen.
  • 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: Hanøy
Triple: [Askøy Municipality, hasIsland, Hanøy]
Generated description
Hanøy is a small Norwegian island that forms part of Askøy Municipality in Vestland county.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hanøy
Target entity description: Hanøy is a small Norwegian island that forms part of Askøy Municipality in Vestland county.
  • A. Florø
    Florø is a coastal town in western Norway known as the country’s westernmost town and a traditional center for fishing and maritime industries.
  • B. Ålesund
    Ålesund is a coastal Norwegian city renowned for its distinctive Art Nouveau architecture and location across several islands in Western Norway.
  • C. Bodø
    Bodø is a coastal city in northern Norway known as a regional hub for culture, transport, and access to Arctic nature.
  • D. Tromsø
    Tromsø is a city in northern Norway known for its Arctic location, vibrant cultural scene, and prominence as a viewing spot for the Northern Lights.
  • E. Stavanger
    Stavanger is a coastal city in southwestern Norway known for its oil industry hub status, historic wooden houses, and proximity to natural attractions like the Lysefjord and Preikestolen.
  • 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_69d87f1bb0988190b490d273dbf3fd03 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e21a05e68881908319454a478cdda5 completed April 17, 2026, 11:31 a.m.
NED1 Entity disambiguation (via context triple) batch_6a050d5b83cc8190ba333d90973335a9 completed May 13, 2026, 11:46 p.m.
NEDg Description generation batch_6a050efd8fe8819094f7a7a1a5edf4c5 completed May 13, 2026, 11:53 p.m.
NED2 Entity disambiguation (via description) batch_6a050f66fd6c8190a7e5750f214018b4 completed May 13, 2026, 11:55 p.m.
Created at: April 10, 2026, 5:01 a.m.