Triple

T14055904
Position Surface form Disambiguated ID Type / Status
Subject Frederiksstaden E338218 entity
Predicate hasPart P35 FINISHED
Object Amaliegade E338223 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: Amaliegade | Statement: [Frederiksstaden, hasPart, Amaliegade]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Amaliegade
Context triple: [Frederiksstaden, hasPart, Amaliegade]
  • A. Amaliegade chosen
    Amaliegade is a historic street in central Copenhagen, Denmark, known for its elegant 18th-century townhouses and proximity to the royal Amalienborg Palace.
  • B. Humlegården
    Humlegården is a large historic park in central Stockholm known for its green spaces, walking paths, and recreational areas.
  • C. Ålsgårde
    Ålsgårde is a coastal town in North Zealand, Denmark, known for its residential areas and proximity to the Øresund Strait.
  • D. Egeskov
    Egeskov is a village on the island of Funen in Denmark best known for the nearby Renaissance water castle Egeskov Castle, one of Europe’s best-preserved moated castles.
  • E. Koldinghus
    Koldinghus is a historic royal castle and museum in the Danish city of Kolding, known for its dramatic ruin-restoration architecture and cultural exhibitions.
  • 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_69d81c67ba6c819091935650dfb3b895 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de3c8d1aa48190a5055d15d9fa220c completed April 14, 2026, 1:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcb6608cf8819087ed5d890b82650a completed May 7, 2026, 3:57 p.m.
Created at: April 9, 2026, 10:20 p.m.