Triple
T32346774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rájec-Jestřebí |
E826482
|
entity |
| Predicate | hasGreenhouseCollection |
P180073
|
FINISHED |
| Object | camellias in Rájec-Jestřebí chateau greenhouse |
—
|
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: camellias in Rájec-Jestřebí chateau greenhouse | Statement: [Rájec-Jestřebí, hasGreenhouseCollection, camellias in Rájec-Jestřebí chateau greenhouse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGreenhouseCollection Context triple: [Rájec-Jestřebí, hasGreenhouseCollection, camellias in Rájec-Jestřebí chateau greenhouse]
-
A.
hasGreenhouse
Indicates that an entity possesses or includes a greenhouse structure or facility.
-
B.
hasGreenhousesCount
Indicates the number of greenhouses associated with or present at an entity.
-
C.
hasNumberOfPlantCollections
Indicates the quantity of distinct plant collections associated with an entity.
-
D.
hasGardenType
Indicates that an entity possesses or is associated with a garden of a specified type.
-
E.
containsGarden
Indicates that one entity includes or has a garden within its area or boundaries.
- F. None of above. chosen
Provenance (4 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_69f34914dfc48190a390cd0720d9e86f |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f7308a096081909d66a56f3c926806 |
completed | May 3, 2026, 11:24 a.m. |
| PD | Predicate disambiguation | batch_69f72a00c5f081908b6539d15baf4e12 |
completed | May 3, 2026, 10:57 a.m. |
| PDg | Predicate description generation | batch_69f730890a008190a882f7828f1c9162 |
completed | May 3, 2026, 11:24 a.m. |
Created at: May 1, 2026, 12:48 a.m.