Triple

T13953824
Position Surface form Disambiguated ID Type / Status
Subject Femundsmarka National Park E335602 entity
Predicate hasWaterBody P165 FINISHED
Object Ljøsnåa
Ljøsnåa is a river or stream located within Norway’s Femundsmarka National Park, known for its remote, pristine wilderness.
E1086634 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: Ljøsnåa | Statement: [Femundsmarka National Park, hasWaterBody, Ljøsnåa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ljøsnåa
Context triple: [Femundsmarka National Park, hasWaterBody, Ljøsnåa]
  • A. Kjeldebotn
    Kjeldebotn is a small village in northern Norway that forms part of the municipality of Ballangen in Nordland county.
  • B. Sørenga
    Sørenga is a modern waterfront neighborhood in Oslo, Norway, known for its residential developments, seaside promenade, and popular public seawater pool and beach.
  • C. Finnvollheia
    Finnvollheia is a mountain that forms the highest point in the Fosen district of Trøndelag, Norway.
  • D. Asmaløy
    Asmaløy is one of the main inhabited islands in the Hvaler archipelago in southeastern Norway, known for its coastal scenery and holiday homes.
  • E. Verdalsøra
    Verdalsøra is a small town in Trøndelag county, Norway, known for its riverside setting and role as a local commercial and service hub.
  • 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: Ljøsnåa
Triple: [Femundsmarka National Park, hasWaterBody, Ljøsnåa]
Generated description
Ljøsnåa is a river or stream located within Norway’s Femundsmarka National Park, known for its remote, pristine wilderness.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ljøsnåa
Target entity description: Ljøsnåa is a river or stream located within Norway’s Femundsmarka National Park, known for its remote, pristine wilderness.
  • A. Kjeldebotn
    Kjeldebotn is a small village in northern Norway that forms part of the municipality of Ballangen in Nordland county.
  • B. Sørenga
    Sørenga is a modern waterfront neighborhood in Oslo, Norway, known for its residential developments, seaside promenade, and popular public seawater pool and beach.
  • C. Finnvollheia
    Finnvollheia is a mountain that forms the highest point in the Fosen district of Trøndelag, Norway.
  • D. Asmaløy
    Asmaløy is one of the main inhabited islands in the Hvaler archipelago in southeastern Norway, known for its coastal scenery and holiday homes.
  • E. Verdalsøra
    Verdalsøra is a small town in Trøndelag county, Norway, known for its riverside setting and role as a local commercial and service hub.
  • 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_69d81c6081b88190b53e317c3370c8fe completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2e146720819085d0f5eae558b7a4 completed April 14, 2026, 12:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd192d09e481909ba3b7522cf661a6 completed May 7, 2026, 10:58 p.m.
NEDg Description generation batch_69fd2315cf6881908fc83b273c966cae completed May 7, 2026, 11:41 p.m.
NED2 Entity disambiguation (via description) batch_69fd238d6a7c8190980388e9027e3a72 completed May 7, 2026, 11:43 p.m.
Created at: April 9, 2026, 10:17 p.m.