Triple

T13866091
Position Surface form Disambiguated ID Type / Status
Subject Minnesund E333330 entity
Predicate near P350 FINISHED
Object Eidsvoll town E94298 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: Eidsvoll town | Statement: [Minnesund, near, Eidsvoll town]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eidsvoll town
Context triple: [Minnesund, near, Eidsvoll town]
  • A. Eidsvoll chosen
    Eidsvoll is a historic Norwegian town best known as the site where Norway’s constitution was drafted and signed in 1814.
  • B. Fredrikstad
    Fredrikstad is a coastal city in southeastern Norway known for its well-preserved fortified old town and role as a regional educational and commercial center.
  • C. Eidsvoll municipality
    Eidsvoll municipality is a historic municipality in Viken county, Norway, best known as the site where the Norwegian Constitution was signed in 1814.
  • D. Nittedal
    Nittedal is a municipality in Viken county, Norway, known for its forested landscapes and role as a commuter area north of Oslo.
  • E. Smestad
    Smestad is a residential neighborhood in Oslo, Norway, known for its affluent housing and proximity to green areas and good public transport.
  • 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_69d81c5ced9c8190b0e9bcc6effe5959 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de05c419d481909230e8879b6dab5c completed April 14, 2026, 9:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c1039128819086cfe9f966b9f142 completed May 3, 2026, 9:41 p.m.
Created at: April 9, 2026, 10:14 p.m.