Triple

T7591583
Position Surface form Disambiguated ID Type / Status
Subject South Funen Archipelago E179746 entity
Predicate hasFerryConnectionsWith P1831 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: [South Funen Archipelago, hasFerryConnectionsWith, Rudkøbing]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rudkøbing
Context triple: [South Funen Archipelago, hasFerryConnectionsWith, 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. Tønder
    Tønder is a historic market town in southern Denmark near the German border, known for its well-preserved old town and cultural heritage.
  • 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_69c69f335248819093c1006f30513708 completed March 27, 2026, 3:16 p.m.
NER Named-entity recognition batch_69c701731a288190b53ffc546a2f47d7 completed March 27, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c98564d32881908ebdeb2aa41da4f7 completed March 29, 2026, 8:02 p.m.
Created at: March 27, 2026, 3:53 p.m.