Triple

T15244657
Position Surface form Disambiguated ID Type / Status
Subject Hurtigruten AS E364347 entity
Predicate hasShip P14595 FINISHED
Object MS Nordnorge
MS Nordnorge is a Norwegian coastal passenger and cruise ship operated on the Hurtigruten coastal route, known for voyages along Norway’s fjords and Arctic coastline.
E1146198 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: MS Nordnorge | Statement: [Hurtigruten AS, hasShip, MS Nordnorge]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MS Nordnorge
Context triple: [Hurtigruten AS, hasShip, MS Nordnorge]
  • A. Nordlandet
    Nordlandet is one of the main islands and districts of the coastal Norwegian city of Kristiansund.
  • B. MS Nordkapp
    MS Nordkapp is a Norwegian coastal passenger and cruise ship operated on the Hurtigruten route along Norway’s coastline.
  • C. Randesund
    Randesund is a coastal district of Kristiansand in southern Norway, known for its scenic archipelago, beaches, and recreational outdoor areas.
  • D. Nordre Land
    Nordre Land is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and agricultural landscape in the traditional district of Land.
  • E. Nord-Sel
    Nord-Sel is a small village in Innlandet county, Norway, situated within the mountainous Sel municipality in the Gudbrandsdalen valley.
  • 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: MS Nordnorge
Triple: [Hurtigruten AS, hasShip, MS Nordnorge]
Generated description
MS Nordnorge is a Norwegian coastal passenger and cruise ship operated on the Hurtigruten coastal route, known for voyages along Norway’s fjords and Arctic coastline.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: MS Nordnorge
Target entity description: MS Nordnorge is a Norwegian coastal passenger and cruise ship operated on the Hurtigruten coastal route, known for voyages along Norway’s fjords and Arctic coastline.
  • A. Nordlandet
    Nordlandet is one of the main islands and districts of the coastal Norwegian city of Kristiansund.
  • B. MS Nordkapp
    MS Nordkapp is a Norwegian coastal passenger and cruise ship operated on the Hurtigruten route along Norway’s coastline.
  • C. Randesund
    Randesund is a coastal district of Kristiansand in southern Norway, known for its scenic archipelago, beaches, and recreational outdoor areas.
  • D. Nordre Land
    Nordre Land is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and agricultural landscape in the traditional district of Land.
  • E. Nord-Sel
    Nord-Sel is a small village in Innlandet county, Norway, situated within the mountainous Sel municipality in the Gudbrandsdalen valley.
  • 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_69d85a0dde7481908fc64d1e82d5d20d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e007f306f08190be448b215d6c9b6c completed April 15, 2026, 9:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fee5f184d481909eb4294ee3648226 completed May 9, 2026, 7:44 a.m.
NEDg Description generation batch_69fee7eabf908190b9248f397319eb6b completed May 9, 2026, 7:53 a.m.
NED2 Entity disambiguation (via description) batch_69fee83bbff481908e297e2c4b2811fb completed May 9, 2026, 7:54 a.m.
Created at: April 10, 2026, 3:13 a.m.