Triple
T32186490
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beschorneria |
E822119
|
entity |
| Predicate | cultivarUse |
P51056
|
FINISHED |
| Object | architectural plant in landscape design |
—
|
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: architectural plant in landscape design | Statement: [Beschorneria, cultivarUse, architectural plant in landscape design]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cultivarUse Context triple: [Beschorneria, cultivarUse, architectural plant in landscape design]
-
A.
plantUse
chosen
Indicates that a plant is used for a particular purpose, function, or application.
-
B.
cultivationType
Indicates the method or system by which something (typically crops or land) is cultivated or farmed.
-
C.
cultivatedFor
Indicates that one entity is intentionally grown, raised, or developed for the benefit, use, or purpose of another entity.
-
D.
isCultivatedAs
Indicates that one entity is intentionally grown, tended, or produced by another as a crop, resource, or cultivated organism.
-
E.
cultivatedSpecies
Indicates that one entity is a species that is intentionally grown or cultivated by another entity.
- 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_69f3490819cc81909bae1f8ce99423c5 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6babadb3481908b49400b3ab42a7c |
completed | May 3, 2026, 3:02 a.m. |
| PD | Predicate disambiguation | batch_69f6b6293188819080d5041ca0adb969 |
completed | May 3, 2026, 2:42 a.m. |
Created at: May 1, 2026, 12:35 a.m.