Triple

T11240334
Position Surface form Disambiguated ID Type / Status
Subject Korsholm E266054 entity
Predicate hasSwedishName P11737 FINISHED
Object Korsholm E266054 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: Korsholm | Statement: [Korsholm, hasSwedishName, Korsholm]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Korsholm
Context triple: [Korsholm, hasSwedishName, Korsholm]
  • A. Korsholm chosen
    Korsholm is a coastal municipality in western Finland, known for its largely Swedish-speaking population and proximity to the city of Vaasa in the Ostrobothnia region.
  • B. Rudkøbing
    Rudkøbing is a small historic town on the Danish island of Langeland, known for its well-preserved old streets and as the birthplace of physicist Hans Christian Ørsted.
  • C. Næstved
    Næstved is a historic market town and commercial center in southern Denmark, located on the island of Zealand.
  • D. Oksbøl
    Oksbøl is a town in southwestern Jutland, Denmark, known for its military training areas and historical role as a garrison location.
  • E. Hellebæk
    Hellebæk is a coastal town in northeastern Zealand, Denmark, known for its scenic setting near Helsingør and its historic industrial and residential architecture.
  • 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_69d6aac656d48190b275efaa7d6074ee completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e919eaf48190a1457851cfc56afb completed April 9, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5b795f7948190a0dd53e8e034fe58 completed April 20, 2026, 5:20 a.m.
Created at: April 8, 2026, 9:30 p.m.