Triple

T2301512
Position Surface form Disambiguated ID Type / Status
Subject Sieges of Fredriksten fortress E51741 entity
Predicate relatedTo P37 FINISHED
Object History of Østfold E96296 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: History of Østfold | Statement: [Sieges of Fredriksten fortress, relatedTo, History of Østfold]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: History of Østfold
Context triple: [Sieges of Fredriksten fortress, relatedTo, History of Østfold]
  • A. Østfold chosen
    Østfold is a former county in southeastern Norway known for its coastal landscape along the Oslofjord, historic fortresses, and proximity to the Swedish border.
  • B. Haderslev
    Haderslev is a historic town in southern Denmark known for its medieval cathedral, old town center, and role as a regional cultural and administrative hub.
  • C. Hellebæk
    Hellebæk is a coastal town in northeastern Zealand, Denmark, known for its scenic setting near Helsingør and its historic industrial and residential architecture.
  • D. Rødovre
    Rødovre is a suburban municipality in the Capital Region of Denmark, located just west of central Copenhagen.
  • E. Østlandet
    Østlandet is the most populous region of southeastern Norway, encompassing the capital city Oslo and surrounding inland and coastal areas.
  • 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_69a88b0a9f248190bcff941463d8f65a completed March 4, 2026, 7:42 p.m.
NER Named-entity recognition batch_69abc5ef51948190ae828d8ee02feb75 completed March 7, 2026, 6:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae7f31356c81909c563d88d472e05f completed March 9, 2026, 8:05 a.m.
Created at: March 4, 2026, 7:49 p.m.