Triple
T8090409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shinjuku Gyoen National Garden |
E188843
|
entity |
| Predicate | hasNumberOfCherryTrees |
P25753
|
FINISHED |
| Object | over 1,000 cherry trees |
—
|
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: over 1,000 cherry trees | Statement: [Shinjuku Gyoen National Garden, hasNumberOfCherryTrees, over 1,000 cherry trees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfCherryTrees Context triple: [Shinjuku Gyoen National Garden, hasNumberOfCherryTrees, over 1,000 cherry trees]
-
A.
hasCherryTreesPlantedSince
Indicates that cherry trees have been planted on or at an entity starting from a specified point in time and continuing thereafter.
-
B.
isCherrySpecies
Indicates that one entity is a biological species classified as a type of cherry in relation to another entity.
-
C.
hasTrees
Indicates that something possesses or contains one or more trees.
-
D.
hasCherryTreeVarieties
Indicates that an entity possesses or includes multiple varieties of cherry trees.
-
E.
numberOfTrees
chosen
Indicates the count or quantity of trees associated with a given entity or context.
- 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.