Triple
T23906845
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Norfolk Botanical Garden |
E601222
|
entity |
| Predicate | hasNumberOfPlants |
P57653
|
FINISHED |
| Object | more than 60,000 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: more than 60,000 plants | Statement: [Norfolk Botanical Garden, hasNumberOfPlants, more than 60,000 plants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfPlants Context triple: [Norfolk Botanical Garden, hasNumberOfPlants, more than 60,000 plants]
-
A.
numberOfPlants
chosen
Indicates the total count of plants associated with a given entity or context.
-
B.
containsPlantsWith
Indicates that one entity includes or holds within it one or more plant entities.
-
C.
hasPlantNumber
Indicates that an entity is associated with a specific plant identifier or plant number.
-
D.
plantCollection
Indicates that one entity maintains or possesses a collection of plants, typically grouped or curated as a set.
-
E.
numberOfCrops
Indicates the quantity or count of crops 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_69e295364a488190bcac702e9bb7f764 |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f1ce91e6088190b85b534ab361f888 |
completed | April 29, 2026, 9:25 a.m. |
| PD | Predicate disambiguation | batch_69f1614e24b48190a1c8fb5b7c75ee0f |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:35 p.m.