Triple
T24035850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rhoon Castle |
E595229
|
entity |
| Predicate | hasPicturesqueSetting |
P6652
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Rhoon Castle, hasPicturesqueSetting, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPicturesqueSetting Context triple: [Rhoon Castle, hasPicturesqueSetting, true]
-
A.
hasScenicValue
chosen
Indicates that something possesses notable aesthetic or visual appeal, often due to its natural beauty or pleasing surroundings.
-
B.
isPartOfScenicVista
Indicates that something is included within, or contributes to, a larger scenic vista or panoramic view.
-
C.
hasScenicViewOf
Indicates that one entity offers a visually appealing or picturesque view of another entity.
-
D.
hasPhotogenicFeature
Indicates that an entity possesses a visual characteristic or attribute that is especially attractive or appealing when photographed.
-
E.
usesImageryOf
Indicates that one entity employs or incorporates visual or sensory imagery that depicts, references, or symbolically represents another entity.
- 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_69e288bf45f08190a1b6ed8cd0b9e86b |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1d8d43884819093e9207a99ae2a70 |
completed | April 29, 2026, 10:09 a.m. |
| PD | Predicate disambiguation | batch_69f1764345388190a3102b62ddb729b4 |
completed | April 29, 2026, 3:08 a.m. |
Created at: April 17, 2026, 9:56 p.m.