Triple
T38703024
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | sagarifuji (hanging wisteria) of Fujiwara |
E950189
|
entity |
| Predicate | hasPlantSpeciesMotif |
P7837
|
FINISHED |
| Object | wisteria |
—
|
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: wisteria | Statement: [sagarifuji (hanging wisteria) of Fujiwara, hasPlantSpeciesMotif, wisteria]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPlantSpeciesMotif Context triple: [sagarifuji (hanging wisteria) of Fujiwara, hasPlantSpeciesMotif, wisteria]
-
A.
hasPlantSymbol
chosen
Indicates that an entity is associated with or represented by a particular plant as its symbolic emblem or sign.
-
B.
hasPlantPart
Indicates that one entity includes, contains, or is composed of a specific plant part of another entity.
-
C.
hasTypeOfMotif
Indicates that one entity features or is characterized by a specific kind or category of motif.
-
D.
isBotanical
Indicates that something pertains to plants or plant science, such as being derived from, related to, or characteristic of botanical life or botany.
-
E.
usesMotifsFrom
Indicates that one entity incorporates or draws upon recurring themes, patterns, or elements that originate from 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_69f76f0124408190bb39c3040734846b |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fe8ddf70e48190a917eb9e8f7b6966 |
completed | May 9, 2026, 1:29 a.m. |
| PD | Predicate disambiguation | batch_69fe87ef94dc81909bb00ec8d6de9bcd |
completed | May 9, 2026, 1:03 a.m. |
Created at: May 3, 2026, 4:33 p.m.