Triple
T21976982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marken lighthouse |
E542729
|
entity |
| Predicate | photographicSubjectType |
P62927
|
FINISHED |
| Object | landscape photography |
—
|
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: landscape photography | Statement: [Marken lighthouse, photographicSubjectType, landscape photography]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: photographicSubjectType Context triple: [Marken lighthouse, photographicSubjectType, landscape photography]
-
A.
isPhotographicSubject
Indicates that an entity serves as the subject or main focus captured in a photograph taken by another entity.
-
B.
depictedSubject
Indicates that one entity visually represents or portrays another entity as its subject in an image or depiction.
-
C.
photographyGenre
chosen
Indicates the specific genre or style of photography that characterizes a photographic work or activity.
-
D.
typicalStillType
Indicates that something represents the usual or characteristic form, style, or configuration that an entity typically has or uses.
-
E.
fieldOfDepiction
Indicates that one entity serves as the subject matter or thematic focus depicted within another entity, such as an image, artwork, or representation.
- 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_69e0c48070988190909db97667b9a0ac |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f12489889c81909c847cf2f6808d85 |
completed | April 28, 2026, 9:20 p.m. |
| PD | Predicate disambiguation | batch_69e6f6154e408190acc5b2c278acaff4 |
completed | April 21, 2026, 3:59 a.m. |
Created at: April 16, 2026, 8:03 p.m.