Triple

T2945486
Position Surface form Disambiguated ID Type / Status
Subject Lofoten E79490 entity
Predicate hasMainTown P14082 FINISHED
Object Svolvær
Svolvær is a coastal town in northern Norway that serves as a key fishing, tourism, and transport hub in the Lofoten archipelago.
 E323764 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: Svolvær | Statement: [Lofoten, hasMainTown, Svolvær]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Svolvær
Context triple: [Lofoten, hasMainTown, Svolvær]
  • A. Røst
    Røst is a small, remote island and fishing community in northern Norway, known for its dramatic coastal scenery, rich seabird colonies, and traditional cod fisheries.
  • B. Nordfjordeid
    Nordfjordeid is a village in western Norway known as a regional center in Nordfjord and the birthplace of mathematician Sophus Lie.
  • C. Bardufoss
    Bardufoss is a town in northern Norway known for its military base, including the main headquarters of the Norwegian Army in the region, and its nearby airport.
  • D. Haugesund
    Haugesund is a coastal city in southwestern Norway known for its maritime heritage, shipbuilding industry, and annual film and jazz festivals.
  • E. Rolvsøy
    Rolvsøy is a district and former municipality that now forms part of the city of Fredrikstad in Viken county, 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: Svolvær
Triple: [Lofoten, hasMainTown, Svolvær]
Generated description
Svolvær is a coastal town in northern Norway that serves as a key fishing, tourism, and transport hub in the Lofoten archipelago.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Svolvær
Target entity description: Svolvær is a coastal town in northern Norway that serves as a key fishing, tourism, and transport hub in the Lofoten archipelago.
  • A. Røst
    Røst is a small, remote island and fishing community in northern Norway, known for its dramatic coastal scenery, rich seabird colonies, and traditional cod fisheries.
  • B. Nordfjordeid
    Nordfjordeid is a village in western Norway known as a regional center in Nordfjord and the birthplace of mathematician Sophus Lie.
  • C. Bardufoss
    Bardufoss is a town in northern Norway known for its military base, including the main headquarters of the Norwegian Army in the region, and its nearby airport.
  • D. Haugesund
    Haugesund is a coastal city in southwestern Norway known for its maritime heritage, shipbuilding industry, and annual film and jazz festivals.
  • E. Rolvsøy
    Rolvsøy is a district and former municipality that now forms part of the city of Fredrikstad in Viken county, 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_69ad8b1089588190b74d9e2505e45762 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad98b2752481908ec6f9a9cc24c0a7 completed March 8, 2026, 3:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1eedb51b88190b7a009d45361fd32 completed March 11, 2026, 10:38 p.m.
NEDg Description generation batch_69b1f2fd518881908fe555d2869b1d59 completed March 11, 2026, 10:55 p.m.
NED2 Entity disambiguation (via description) batch_69b1f35c16548190b3ec9764cf812497 completed March 11, 2026, 10:57 p.m.
Created at: March 8, 2026, 2:56 p.m.