Triple

T17657870
Position Surface form Disambiguated ID Type / Status
Subject Hurum E440171 entity
Predicate contains P35 FINISHED
Object Hurumlandet
Hurumlandet is a peninsula in Viken county, Norway, known for its coastal landscapes along the Oslofjord and Drammensfjord.
E1281261 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: Hurumlandet | Statement: [Hurum, contains, Hurumlandet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hurumlandet
Context triple: [Hurum, contains, Hurumlandet]
  • A. Hadeland
    Hadeland is a traditional rural district in southeastern Norway known for its agricultural landscape, historic churches, and the Hadeland Glassverk glassworks.
  • B. 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.
  • C. Dyrholm
    Dyrholm is a Danish surname most notably borne by acclaimed actress and singer Trine Dyrholm.
  • D. Hageland
    Hageland is a hilly, rural region in the eastern part of Flemish Brabant in Belgium, known for its orchards, vineyards, and scenic landscapes.
  • E. Haugalandet
    Haugalandet is a coastal region in western Norway centered around the town of Haugesund, known for its maritime heritage and North Sea industries.
  • 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: Hurumlandet
Triple: [Hurum, contains, Hurumlandet]
Generated description
Hurumlandet is a peninsula in Viken county, Norway, known for its coastal landscapes along the Oslofjord and Drammensfjord.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Hurumlandet
Target entity description: Hurumlandet is a peninsula in Viken county, Norway, known for its coastal landscapes along the Oslofjord and Drammensfjord.
  • A. Hadeland
    Hadeland is a traditional rural district in southeastern Norway known for its agricultural landscape, historic churches, and the Hadeland Glassverk glassworks.
  • B. 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.
  • C. Dyrholm
    Dyrholm is a Danish surname most notably borne by acclaimed actress and singer Trine Dyrholm.
  • D. Hageland
    Hageland is a hilly, rural region in the eastern part of Flemish Brabant in Belgium, known for its orchards, vineyards, and scenic landscapes.
  • E. Haugalandet
    Haugalandet is a coastal region in western Norway centered around the town of Haugesund, known for its maritime heritage and North Sea industries.
  • 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_69d8b9e87e18819087104a44dc4dc5b1 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e46ea3b4cc81908eec7032cf221d49 completed April 19, 2026, 5:56 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0216584eb88190afa898efae284934 completed May 11, 2026, 5:48 p.m.
NEDg Description generation batch_6a0218a828548190b492e721e546f224 completed May 11, 2026, 5:58 p.m.
NED2 Entity disambiguation (via description) batch_6a02193505ec8190800570487768cf07 completed May 11, 2026, 6 p.m.
Created at: April 10, 2026, 9:28 a.m.