Triple
T8090419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shinjuku Gyoen National Garden |
E188843
|
entity |
| Predicate | greenhouseFeatures |
P22782
|
FINISHED |
| Object | tropical plants |
—
|
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: tropical plants | Statement: [Shinjuku Gyoen National Garden, greenhouseFeatures, tropical plants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: greenhouseFeatures Context triple: [Shinjuku Gyoen National Garden, greenhouseFeatures, tropical plants]
-
A.
hasGreenhouse
Indicates that an entity possesses or includes a greenhouse structure or facility.
-
B.
gardenFeature
chosen
Indicates that one entity serves as a feature, element, or component within a garden associated with another entity.
-
C.
roofFeature
Indicates that one entity is a feature, element, or characteristic that is part of or associated with a roof.
-
D.
hasGreenhouseEffect
Indicates that one entity causes or contributes to a greenhouse effect on another entity, typically by trapping heat through atmospheric or environmental mechanisms.
-
E.
featuresHabitat
Indicates that something includes or provides a particular habitat as part of its characteristics or environment.
- 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_69ca82b7b3e88190b9041ab0ef28b3cb |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb421fb8348190b6495394d498d3f4 |
completed | March 31, 2026, 3:40 a.m. |
| PD | Predicate disambiguation | batch_69cb04a14cd88190a79ed26cbeec1c33 |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:29 p.m.