Triple

T21545410
Position Surface form Disambiguated ID Type / Status
Subject Oslomarka E531610 entity
Predicate hasPart P35 FINISHED
Object Nordmarka NE NERFINISHED

How this triple was built (2 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: Nordmarka | Statement: [Oslomarka, hasPart, Nordmarka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nordmarka
Context triple: [Oslomarka, hasPart, Nordmarka]
  • A. Nordmarka chosen
    Nordmarka is a large forested recreational area north of Oslo, Norway, popular for hiking, skiing, and outdoor activities.
  • B. Jostedalen
    Jostedalen is a valley and former municipality in western Norway, known for its dramatic glacial landscapes and proximity to the Jostedalsbreen glacier.
  • C. Hattfjelldal
    Hattfjelldal is a sparsely populated municipality in Nordland county, Norway, known for its mountainous terrain, extensive wilderness areas, and strong Sami cultural heritage.
  • D. Hallingdal
    Hallingdal is a major valley and traditional district in southeastern Norway, known for its river, ski resorts, and rich folk culture.
  • E. Lyngen region
    The Lyngen region is a scenic area in Troms, northern Norway, known for its dramatic fjords, alpine peaks, and popular outdoor activities like skiing and hiking.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c45f17148190949c330ab9c27706 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69eeb58e38808190888f3501cf4fff7c completed April 27, 2026, 1:02 a.m.
Created at: April 16, 2026, 6:28 p.m.