Triple

T10450625
Position Surface form Disambiguated ID Type / Status
Subject Akershus county E246411 entity
Predicate hadMunicipality P84684 FINISHED
Object Bærum E186288 NE FINISHED

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: [Akershus county, hadMunicipality, Bærum]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bærum
Context triple: [Akershus county, hadMunicipality, 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 (3 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_69d381c04fe08190957c26c526a3b05a completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d5190da7f081908c38b5964a567e37 completed April 7, 2026, 2:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f1658e03a8819098ea2ac2f818a61a completed April 29, 2026, 1:57 a.m.
Created at: April 6, 2026, 12:17 p.m.