Triple
T18184738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fisker |
E435380
|
entity |
| Predicate | hasNotableDomainOfBearers |
P2531
|
FINISHED |
| Object | Danish architecture |
—
|
LITERAL 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: Danish architecture | Statement: [Fisker, hasNotableDomainOfBearers, Danish architecture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableDomainOfBearers Context triple: [Fisker, hasNotableDomainOfBearers, Danish architecture]
-
A.
hasNotableFieldOfBearers
chosen
Indicates that the entities share a significant or distinguished area of activity, expertise, or achievement associated with their bearers.
-
B.
hasNotableBearersType
Indicates that an entity has notable bearers belonging to a specified type or category.
-
C.
hasNotableBearer
Indicates that an entity (such as a name, title, or identifier) is borne by at least one notable person or entity.
-
D.
hasNotableBearersCount
Indicates the number of notable individuals or entities that bear or are associated with the subject.
-
E.
hasNotableBearerFamily
Indicates that a family is recognized for having at least one notable or distinguished member associated with it.
- F. None of above.
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_69d8b90c7ec081909b4694ccecb449c6 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4dffdccd881908da772db78b9d081 |
completed | April 19, 2026, 2 p.m. |
| PD | Predicate disambiguation | batch_69e4331e92408190ad607ba4956a3897 |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:31 a.m.