Triple

T23543840
Position Surface form Disambiguated ID Type / Status
Subject Ulsrud E577831 entity
Predicate near P350 FINISHED
Object Østmarka forest area 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: Østmarka forest area | Statement: [Ulsrud, near, Østmarka forest area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Østmarka forest area
Context triple: [Ulsrud, near, Østmarka forest area]
  • A. Østmarka forest chosen
    Østmarka forest is a large, hilly woodland and recreational area on the eastern outskirts of Oslo, Norway, known for its lakes, hiking trails, and outdoor activities.
  • B. Kjekstadmarka forest area
    Kjekstadmarka forest area is a popular woodland and outdoor recreation area in southeastern Norway known for its hiking, skiing, and natural landscapes.
  • C. Kvamskogen
    Kvamskogen is a popular mountainous recreational area in western Norway known for its ski resorts, cabins, and outdoor activities.
  • D. Kolmården forest region
    Kolmården forest region is a large, historically significant woodland and hilly landscape in eastern Sweden known for its natural beauty and outdoor recreation.
  • E. Hälsingland forests
    Hälsingland forests are a vast, sparsely populated woodland region in central Sweden known for their boreal landscapes, wildlife, and traditional rural settlements.
  • 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_69e245f9d5d08190a4a20004e1784e20 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f1ae1dbe188190bc4afe7bfa7cda0f completed April 29, 2026, 7:07 a.m.
Created at: April 17, 2026, 6:11 p.m.