Triple

T15760399
Position Surface form Disambiguated ID Type / Status
Subject Ibestad E382080 entity
Predicate administrativeCentre P1474 FINISHED
Object Hamnvåg
Hamnvåg is a small village in Troms og Finnmark county, Norway, known for serving as the local hub of municipal services for the surrounding island community.
E1213601 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: Hamnvåg | Statement: [Ibestad, administrativeCentre, Hamnvåg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hamnvåg
Context triple: [Ibestad, administrativeCentre, Hamnvåg]
  • A. Hundvåg
    Hundvåg is an island in southwestern Norway that forms part of the city of Stavanger and is known for its residential areas and coastal landscape.
  • B. Hadsel
    Hadsel is a coastal municipality in Nordland county, Norway, known for encompassing several islands in the Vesterålen archipelago, including parts of Hadseløya, Langøya, and Austvågøya.
  • C. Kårvåg
    Kårvåg is a small coastal village in western Norway, known as a settlement on the island of Averøya in Møre og Romsdal county.
  • D. Sørvågen
    Sørvågen is a small fishing village and tourist destination located on the island of Moskenesøya in Norway’s Lofoten archipelago.
  • E. Vikevåg
    Vikevåg is a village in Rogaland county, Norway, known for its coastal setting and role in local administration and services.
  • 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: Hamnvåg
Triple: [Ibestad, administrativeCentre, Hamnvåg]
Generated description
Hamnvåg is a small village in Troms og Finnmark county, Norway, known for serving as the local hub of municipal services for the surrounding island community.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Hamnvåg
Target entity description: Hamnvåg is a small village in Troms og Finnmark county, Norway, known for serving as the local hub of municipal services for the surrounding island community.
  • A. Hundvåg
    Hundvåg is an island in southwestern Norway that forms part of the city of Stavanger and is known for its residential areas and coastal landscape.
  • B. Hadsel
    Hadsel is a coastal municipality in Nordland county, Norway, known for encompassing several islands in the Vesterålen archipelago, including parts of Hadseløya, Langøya, and Austvågøya.
  • C. Kårvåg
    Kårvåg is a small coastal village in western Norway, known as a settlement on the island of Averøya in Møre og Romsdal county.
  • D. Sørvågen
    Sørvågen is a small fishing village and tourist destination located on the island of Moskenesøya in Norway’s Lofoten archipelago.
  • E. Vikevåg
    Vikevåg is a village in Rogaland county, Norway, known for its coastal setting and role in local administration and services.
  • 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_69d86d9e6b44819085d1f6a969ecb74c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e050b52c548190a0ffa4493a4eb15c completed April 16, 2026, 3 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00456b590c8190949fd23cb5cec1e8 completed May 10, 2026, 8:44 a.m.
NEDg Description generation batch_6a004771e5108190a7fd4f6e274e455a completed May 10, 2026, 8:53 a.m.
NED2 Entity disambiguation (via description) batch_6a00482646c88190a8e3a5299146b504 completed May 10, 2026, 8:56 a.m.
Created at: April 10, 2026, 4:47 a.m.