Triple
T14782995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nyhavn 18 |
E347437
|
entity |
| Predicate | inDistrict |
P29284
|
FINISHED |
| Object | Indre By |
E368543
|
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: Indre By | Statement: [Nyhavn 18, inDistrict, Indre By]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Indre By Context triple: [Nyhavn 18, inDistrict, Indre By]
-
A.
Indre By
chosen
Indre By is the historic city center of Copenhagen, Denmark, known for its cobblestone streets, canals, and many of the capital’s main cultural and architectural landmarks.
-
B.
Nørrebro
Nørrebro is a vibrant, multicultural district in Copenhagen known for its lively street life, diverse communities, and mix of historic and modern urban culture.
-
C.
Frederiksberg
Frederiksberg is an affluent, centrally located municipality in Denmark that forms an enclave within the city of Copenhagen and is known for its parks, cultural institutions, and historic architecture.
-
D.
Nørreport
Nørreport is one of central Copenhagen’s busiest transport hubs, combining metro, S-train, and regional rail services in a major underground station.
-
E.
Vesterbro
Vesterbro is a vibrant, formerly working-class district of Copenhagen known for its trendy bars, restaurants, and cultural scene.
- 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_69d822e9b9e08190bedcc31a163fda82 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deca9de3f48190b7706925e2947cf5 |
completed | April 14, 2026, 11:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff4c2a938081909ccd9fe7c5021dc6 |
completed | May 9, 2026, 3 p.m. |
Created at: April 10, 2026, 1:31 a.m.