Triple

T21545425
Position Surface form Disambiguated ID Type / Status
Subject Oslomarka E531610 entity
Predicate borders P224 FINISHED
Object Hurumlandet 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: Hurumlandet | Statement: [Oslomarka, borders, Hurumlandet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hurumlandet
Context triple: [Oslomarka, borders, Hurumlandet]
  • A. Hurumlandet chosen
    Hurumlandet is a peninsula in Viken county, Norway, known for its coastal landscapes along the Oslofjord and Drammensfjord.
  • B. Hareidlandet
    Hareidlandet is an island on Norway’s western coast known for its rugged coastal landscape and the municipalities of Hareid and Ulstein.
  • C. Hærland
    Hærland is a small village in the former Eidsberg municipality in Østfold county, southeastern Norway.
  • D. Malderen
    Malderen is a village in the municipality of Londerzeel in the Flemish Region of Belgium.
  • E. Hadeland
    Hadeland is a traditional rural district in southeastern Norway known for its agricultural landscape, historic churches, and the Hadeland Glassverk glassworks.
  • 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.