Triple

T9132901
Position Surface form Disambiguated ID Type / Status
Subject Nikolaj Coster-Waldau E219133 entity
Predicate placeOfBirth P1 FINISHED
Object Rudkøbing E286509 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: Rudkøbing | Statement: [Nikolaj Coster-Waldau, placeOfBirth, Rudkøbing]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rudkøbing
Context triple: [Nikolaj Coster-Waldau, placeOfBirth, Rudkøbing]
  • A. Rudkøbing chosen
    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.
  • B. Korsholm
    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.
  • C. Vordingborg
    Vordingborg is a historic coastal town in southern Denmark known for the ruins of Vordingborg Castle and its prominent Goose Tower.
  • D. Hellebæk
    Hellebæk is a coastal town in northeastern Zealand, Denmark, known for its scenic setting near Helsingør and its historic industrial and residential architecture.
  • E. Oksbøl
    Oksbøl is a town in southwestern Jutland, Denmark, known for its military training areas and historical role as a garrison location.
  • 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_69ca83debfc0819095800583e97ab10f completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cca8db7d808190bd22b0e5a6f9c285 completed April 1, 2026, 5:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1bca05c608190935af17d94c567d6 completed April 5, 2026, 1:36 a.m.
Created at: March 30, 2026, 7:18 p.m.