Triple

T15751198
Position Surface form Disambiguated ID Type / Status
Subject Salten E381847 entity
Predicate hasIsland P970 FINISHED
Object Landegode
Landegode is a scenic Norwegian island in Nordland county, known for its rugged coastline, lighthouse, and views toward the nearby city of Bodø.
E1175949 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: Landegode | Statement: [Salten, hasIsland, Landegode]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Landegode
Context triple: [Salten, hasIsland, Landegode]
  • A. Forlandet
    Forlandet is a long, narrow island off the west coast of Spitsbergen in the Svalbard archipelago, known for its protected wilderness and rich Arctic wildlife.
  • B. Bygland
    Bygland is a rural municipality in southern Norway known for its location along the Setesdal valley and the Byglandsfjorden lake.
  • C. Länder
    Länder are the individual federal states that make up the Federal Republic of Germany, each with its own government and significant legislative powers.
  • D. Helleland
    Helleland is a small village in Rogaland county, Norway, situated within the municipality of Eigersund.
  • E. Lokve
    Lokve is a small mountain town in Croatia’s Gorski Kotar region, known for its forests, lakes, and outdoor recreation.
  • 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: Landegode
Triple: [Salten, hasIsland, Landegode]
Generated description
Landegode is a scenic Norwegian island in Nordland county, known for its rugged coastline, lighthouse, and views toward the nearby city of Bodø.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Landegode
Target entity description: Landegode is a scenic Norwegian island in Nordland county, known for its rugged coastline, lighthouse, and views toward the nearby city of Bodø.
  • A. Forlandet
    Forlandet is a long, narrow island off the west coast of Spitsbergen in the Svalbard archipelago, known for its protected wilderness and rich Arctic wildlife.
  • B. Bygland
    Bygland is a rural municipality in southern Norway known for its location along the Setesdal valley and the Byglandsfjorden lake.
  • C. Länder
    Länder are the individual federal states that make up the Federal Republic of Germany, each with its own government and significant legislative powers.
  • D. Helleland
    Helleland is a small village in Rogaland county, Norway, situated within the municipality of Eigersund.
  • E. Lokve
    Lokve is a small mountain town in Croatia’s Gorski Kotar region, known for its forests, lakes, and outdoor recreation.
  • 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_69e05030e31081908c307a8dc7067db4 completed April 16, 2026, 2:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff876d48588190afec7722cca25633 completed May 9, 2026, 7:13 p.m.
NEDg Description generation batch_69ff8b6c44d081908e35ca17b5ce2189 completed May 9, 2026, 7:30 p.m.
NED2 Entity disambiguation (via description) batch_69ff8ca1c1f08190aeb6f7421d54c2de completed May 9, 2026, 7:36 p.m.
Created at: April 10, 2026, 4:47 a.m.