Triple

T21545440
Position Surface form Disambiguated ID Type / Status
Subject Oslomarka E531610 entity
Predicate nearbyMunicipality P4647 FINISHED
Object Bærum 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: Bærum | Statement: [Oslomarka, nearbyMunicipality, Bærum]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bærum
Context triple: [Oslomarka, nearbyMunicipality, Bærum]
  • A. Bærum chosen
    Bærum is a wealthy suburban municipality just west of Oslo, Norway, known for its high standard of living and residential communities.
  • B. Høvik
    Høvik is a suburban residential area and neighborhood in the municipality of Bærum in Viken county, Norway.
  • C. Drammen
    Drammen is a city and municipality in southeastern Norway known for its riverside setting along the Drammenselva and its role as a regional commercial and transport hub.
  • D. Torshov
    Torshov is a residential neighborhood in Oslo, Norway, known for its early 20th-century architecture, green spaces, and vibrant local culture.
  • E. Sokna
    Sokna is an extinct Eastern Berber language formerly spoken around the oasis town of Sokna in central Libya.
  • 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.