Triple
T36129774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Staphyleaceae |
E1044982
|
entity |
| Predicate | floralPartNumber |
P68196
|
FINISHED |
| Object | typically 5-merous perianth |
—
|
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: typically 5-merous perianth | Statement: [Staphyleaceae, floralPartNumber, typically 5-merous perianth]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: floralPartNumber Context triple: [Staphyleaceae, floralPartNumber, typically 5-merous perianth]
-
A.
hasFloralFeature
chosen
Indicates that an entity possesses a specific floral characteristic, structure, or attribute.
-
B.
flowerStructure
Indicates the structural characteristics or organization of a flower, such as the arrangement and form of its parts.
-
C.
petalCount
Indicates the number of petals associated with an entity, typically a flower or floral structure.
-
D.
hasFloralWhorlCount
Indicates the number of floral whorls present in a flower.
-
E.
mainFloralSource
Indicates that one entity serves as the primary floral or plant-based source for another entity (such as a product, substance, or process).
- 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_69f76e356c908190abc6ca1e6a05b011 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7b3e2f3c08190be4fd1ae4fa1266d |
completed | May 3, 2026, 8:45 p.m. |
| PD | Predicate disambiguation | batch_69f7b1bcc47081909fe7d592ac69006c |
completed | May 3, 2026, 8:36 p.m. |
Created at: May 3, 2026, 4:08 p.m.