Triple

T14667447
Position Surface form Disambiguated ID Type / Status
Subject New Harbor E344415 entity
Predicate hasDanishName P58114 FINISHED
Object Nyhavn E68372 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: Nyhavn | Statement: [New Harbor, hasDanishName, Nyhavn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nyhavn
Context triple: [New Harbor, hasDanishName, Nyhavn]
  • A. Nyhavn chosen
    Nyhavn is a historic waterfront district in central Copenhagen known for its colorful 17th-century townhouses, canalside restaurants, and vibrant harbor atmosphere.
  • B. Amaliehaven
    Amaliehaven is a small waterfront park and fountain garden in central Copenhagen, known for its formal design and views of the harbor and Amalienborg Palace.
  • C. Old Port
    Old Port is Portland, Maine’s historic waterfront district known for its cobblestone streets, 19th-century brick buildings, and vibrant shops, restaurants, and nightlife.
  • D. Sydhavn
    Sydhavn is a district in Copenhagen, Denmark, known for its former industrial harbor areas now undergoing redevelopment into residential and commercial neighborhoods.
  • E. Nordhavn
    Nordhavn is a harbor-side district in Copenhagen, Denmark, known for its large-scale urban redevelopment into a modern, sustainable waterfront neighborhood.
  • 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_69d822e283fc8190a0e4c235cf880052 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb54dda1c8190bf16d17e26a2bba6 completed April 14, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe64ec72bc819085fa2c21487f297e completed May 8, 2026, 10:34 p.m.
Created at: April 10, 2026, 1:27 a.m.