Triple

T18927129
Position Surface form Disambiguated ID Type / Status
Subject Guldborgsund Municipality E463002 entity
Predicate seat P75 FINISHED
Object Nykøbing Falster NE NERFINISHED

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: Nykøbing Falster | Statement: [Guldborgsund Municipality, seat, Nykøbing Falster]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nykøbing Falster
Context triple: [Guldborgsund Municipality, seat, Nykøbing Falster]
  • A. Nykøbing Falster chosen
    Nykøbing Falster is a historic market town on the Danish island of Falster, known for its medieval heritage and role as a regional commercial and cultural center.
  • B. Nykøbing Mors
    Nykøbing Mors is a Danish coastal town on the island of Mors, known as its main urban center and a local hub for fishing, trade, and tourism.
  • C. Vordingborg
    Vordingborg is a historic coastal town in southern Denmark known for the ruins of Vordingborg Castle and its prominent Goose Tower.
  • D. Fjerritslev
    Fjerritslev is a small Danish town in the North Jutland region, known historically for its agricultural surroundings and local brewery heritage.
  • E. Vækerø
    Vækerø is a residential and commercial area in Oslo, Norway, located along the western waterfront and known for its mix of housing, offices, and green spaces.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8dcfdbbb881909964fa5a75bd0b48 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5c9bc36588190ae9cc3b8abf8afd4 completed April 20, 2026, 6:37 a.m.
Created at: April 10, 2026, 11:59 a.m.