Triple

T4365560
Position Surface form Disambiguated ID Type / Status
Subject Oppland E98763 entity
Predicate containsPart P35 FINISHED
Object Hadeland E337526 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: Hadeland | Statement: [Oppland, containsPart, Hadeland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hadeland
Context triple: [Oppland, containsPart, Hadeland]
  • A. Hadeland chosen
    Hadeland is a traditional rural district in southeastern Norway known for its agricultural landscape, historic churches, and the Hadeland Glassverk glassworks.
  • B. Haugalandet
    Haugalandet is a coastal region in western Norway centered around the town of Haugesund, known for its maritime heritage and North Sea industries.
  • C. Helgeland
    Helgeland is a coastal region in northern Norway known for its dramatic fjords, islands, and mountain landscapes.
  • D. Nordre Land
    Nordre Land is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and agricultural landscape in the traditional district of Land.
  • E. Numedal
    Numedal is a valley in southeastern Norway known for its traditional wooden architecture, medieval stave churches, and scenic river landscape.
  • 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_69b3454c772081908e20173e379e8ebe completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35200263081909bb326a4d7a8db99 completed March 12, 2026, 11:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69b61352f8308190af30daeaae0bf0d6 completed March 15, 2026, 2:02 a.m.
Created at: March 12, 2026, 11:17 p.m.