Triple

T13798016
Position Surface form Disambiguated ID Type / Status
Subject Hamar, Norway E331565 entity
Predicate hasCulturalAttraction P3114 FINISHED
Object Domkirkeodden E331573 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: Domkirkeodden | Statement: [Hamar, Norway, hasCulturalAttraction, Domkirkeodden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Domkirkeodden
Context triple: [Hamar, Norway, hasCulturalAttraction, Domkirkeodden]
  • A. Domkirkeodden chosen
    Domkirkeodden is a historic museum and cultural heritage site on the shores of Lake Mjøsa in Hamar, Norway, known for its medieval cathedral ruins and distinctive glass protective structure.
  • B. Orkanger
    Orkanger is a town in Trøndelag county, Norway, known as a regional commercial and service hub by the Orkdalsfjorden.
  • C. Mortensrud
    Mortensrud is a residential neighborhood in the Søndre Nordstrand borough of Oslo, Norway, known for its multicultural population and modern church, and served as the terminus of an Oslo Metro line.
  • D. St. Hanshaugen
    St. Hanshaugen is a central borough of Oslo, Norway, known for its large hillside park and vibrant urban residential areas.
  • E. Gjerdrum
    Gjerdrum is a small rural municipality in Viken county, Norway, known for its agricultural landscape and proximity to the Oslo metropolitan area.
  • 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_69d81c58feb08190a77bca8bf7d6d20f completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de025be1f08190aac525d72d7dc0c3 completed April 14, 2026, 9:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7b086d6d48190b823ed0a4403fbc5 completed May 3, 2026, 8:31 p.m.
Created at: April 9, 2026, 10:11 p.m.