Triple
T14820707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nyhavn 71 |
E348442
|
entity |
| Predicate | locatedIn |
P40
|
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: [Nyhavn 71, locatedIn, Nyhavn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nyhavn Context triple: [Nyhavn 71, locatedIn, 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.
Copenhaver
Copenhaver is a surname of likely English or German origin borne by various individuals, including Eleanor Copenhaver.
-
D.
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.
-
E.
Sydhavn
Sydhavn is a district in Copenhagen, Denmark, known for its former industrial harbor areas now undergoing redevelopment into residential and commercial neighborhoods.
- 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_69d822eb8f588190bf53445e730a934f |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decfe64328819083ce42704cf0602d |
completed | April 14, 2026, 11:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fec870cea08190962434fc2647fd67 |
completed | May 9, 2026, 5:38 a.m. |
Created at: April 10, 2026, 1:50 a.m.