Triple
T7559990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nong Nooch Tropical Garden |
E178768
|
entity |
| Predicate | hasThemedGarden |
P12538
|
FINISHED |
| Object | French garden |
—
|
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: French garden | Statement: [Nong Nooch Tropical Garden, hasThemedGarden, French garden]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasThemedGarden Context triple: [Nong Nooch Tropical Garden, hasThemedGarden, French garden]
-
A.
containsGarden
Indicates that one entity includes or has a garden within its area or boundaries.
-
B.
hasGardenType
chosen
Indicates that an entity possesses or is associated with a garden of a specified type.
-
C.
hasGardenSquare
Indicates that an entity includes, is adjacent to, or is otherwise associated with a garden square.
-
D.
hasBotanicalGarden
Indicates that one entity possesses, contains, or includes a botanical garden as part of its facilities or domain.
-
E.
hasThemedLand
Indicates that one entity (typically a larger venue or park) includes or is composed of a specific themed land or area as part of its layout or structure.
- 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_69c69f2da22c8190a50942ac20af70e8 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f8dd96488190b4cca25ae8f7f95c |
completed | March 27, 2026, 9:38 p.m. |
| PD | Predicate disambiguation | batch_69c6f4dc485c819080da13e3b7f4f08f |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:50 p.m.