Triple
T12343035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bougainvillea City |
E294277
|
entity |
| Predicate | hasMainFloralSymbol |
P104578
|
FINISHED |
| Object | bougainvillea |
—
|
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: bougainvillea | Statement: [Bougainvillea City, hasMainFloralSymbol, bougainvillea]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMainFloralSymbol Context triple: [Bougainvillea City, hasMainFloralSymbol, bougainvillea]
-
A.
hasFloralFeature
Indicates that an entity possesses a specific floral characteristic, structure, or attribute.
-
B.
hasFlowerColor
Indicates that an entity (typically a plant or flower) possesses a specific flower color.
-
C.
hasFloralRegion
Indicates that one entity possesses or is associated with a specific floral region as a characteristic or component.
-
D.
hasPetalType
Indicates that an entity possesses petals characterized by a specific type or form.
-
E.
hasSpecializedPetal
Indicates that an entity possesses petals that are specialized or modified for a particular function or role.
- F. None of above. chosen
Provenance (4 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_69d6ab6ccbec8190b09e2d357aa80064 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f78a970819086beec3e4da8c49e |
completed | April 10, 2026, 6:20 p.m. |
| PD | Predicate disambiguation | batch_69d93ecb5efc819086a3530282278bb1 |
completed | April 10, 2026, 6:17 p.m. |
| PDg | Predicate description generation | batch_69d93f607a88819089e89fd263ae9937 |
completed | April 10, 2026, 6:20 p.m. |
Created at: April 8, 2026, 9:53 p.m.