Triple

T18113169
Position Surface form Disambiguated ID Type / Status
Subject Lom E433531 entity
Predicate hasPostalCode P222 FINISHED
Object 2687 Bøverdalen 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: 2687 Bøverdalen | Statement: [Lom, hasPostalCode, 2687 Bøverdalen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 2687 Bøverdalen
Context triple: [Lom, hasPostalCode, 2687 Bøverdalen]
  • A. Bøverdalen chosen
    Bøverdalen is a scenic valley in the municipality of Lom in Innlandet county, Norway, known as a gateway to the Jotunheimen mountains and surrounding national parks.
  • B. Bøelva
    Bøelva is a river in Telemark, Norway, known for flowing through the Bø area before emptying into the large lake Norsjø.
  • C. Bøverbru
    Bøverbru is a small village in Innlandet county, Norway, known for its rural setting and role as a local community center within Vestre Toten.
  • D. Bøvra
    Bøvra is a river in Lom Municipality in Innlandet county, Norway, known for flowing through a mountainous valley landscape.
  • E. Bømlo (4613)
    Bømlo (4613) is a municipality in Vestland county, Norway, known for its coastal islands, fishing industry, and maritime heritage.
  • 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_69d8b90916008190a1f110bd7ced5473 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4ddd3fd9c81909bfe95927f7553e3 completed April 19, 2026, 1:51 p.m.
Created at: April 10, 2026, 10:28 a.m.